Cities and climate chnage alt[1]

Cities and Climate Change examines the links between urbanization and climate change, the potentially devastating effects of climate change on urban populations, and the policy responses and practices that are emerging in urban areas.

Over half of the world’s population now live in urban settlements, and the convergence of urbanization and climate change threatens to have an unpre cedented impact on economies, quality of life and social stability. Alongside these threats, however, is an equally compelling set of opportunities. The concentration of people, industries and infrastructure, as well as social and cultural activities, acts as a crucible of innovation – developing ways to reduce greenhouse gas emissions, improve coping mechanisms and reduce vulnerability to climate change impacts.

This new report from the United Nations Human Settlements Programme (UN-Habitat), the world’s leading authority on urban issues, shows how cities can improve the way they operate in order to respond to climate change, and provides practical strategies for strengthening their role as part of the solution. The Global Report on Human Settlements 2011 is the most authoritative and up-to-date global assessment of human settlement conditions and trends. Preceding issues of the report have addressed such topics as Cities in a Globalizing World, The Challenge of Slums, Financing Urban Shelter, Enhancing Urban Safety and Security and Planning Sustainable Cities.

Glo

ba

l rep

or

t on

hu

ma

n settlem

ents 2

01

1 C

ities an

d C

lima

te Ch

an

ge

Cover photos: • Wind turbine in downtown Cleveland, Ohio, US, © Henryk Sadura / Shutterstock • Storm surge barrier in Zeeland, the Netherlands, © Gertje / Shutterstock• Rickshaw drivers taking tourist on a tour in the Houhai lakes area, Beijing, China, © Yadid Levy / Alamy Property• Street scene, Asmara, Eritrea, © Hermes Images / Photolibrary• Aerial view of Rio de Janeiro, Brazil, © Mark Schwettmann / Shutterstock

Urban Development / Spatial Planning / Sustainable Development / Climate Change

Cities and Climate ChangeGlobal report on human settlements 2011

‘This year’s edition of UN-Habitat’s Global Report on Human Settlements elucidates the relationship between urban settlements and climate change,

and suggests how cities and towns that have not yet adopted climate change policies can begin to do so … I commend this report to all concerned with improving

the ability of towns and cities to mitigate climate change and adapt to its impacts.’

From the Foreword by BAN KI-MOON, Secretary-General, United Nations UNITED NATIONS HUMAN SETTLEMENTS PROGRAMME

publ ishing for a sustainable future

w w w . e a r t h s c a n . c o . u k

pu

blish

ing

for a

susta

ina

ble

futu

re

ww

w.e

arth

sc

an

.co

.uk

Earthscan strives to minimize its impact on the environment

CITIES AND CLIMATE CHANGE

CITIES AND CLIMATE CHANGEGLOBAL REPORT ON HUMAN SETTLEMENTS 2011

United Nations Human Settlements Programme

London • Washington, DC

First published in 2011 by Earthscan

Copyright © United Nations Human Settlements Programme (UN-Habitat), 2011

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means,electronic, mechanical, photocopying, recording or otherwise, except as expressly permitted by law, without the prior, written permission ofthe publisher.

Earthscan Ltd, Dunstan House, 14a St Cross Street, London EC1N 8XA, UKEarthscan LLC, 1616 P Street, NW, Washington, DC 20036, USA

Earthscan publishes in association with the International Institute for Environment and Development

For more information on Earthscan publications, see www.earthscan.co.uk or write to [email protected]

United Nations Human Settlements Programme (UN-Habitat)PO Box 30030, GPO Nairobi 00100, KenyaTel: +254 20 762 3120Fax: +254 20 762 3477 / 4266 / 4267Web: www.unhabitat.org

DISCLAIMERThe designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever onthe part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area, or of its authorities, orconcerning delimitation of its frontiers or boundaries, or regarding its economic system or degree of development. The analysis, conclusionsand recommendations of the report do not necessarily reflect the views of the United Nations Human Settlements Programme, the GoverningCouncil of the United Nations Human Settlements Programme or its Member States.

HS Number: HS/1/11E (paperback)HS/2/11E (hardback)

ISBN: 978-1-84971-371-9 (paperback)978-1-84971-370-2 (hardback)978-92-1-131929-3 (UN-Habitat series)978-92-1-132296-5 (UN-Habitat paperback)978-92-1-132297-2 (UN-Habitat hardback)

Typeset by MapSet Ltd, GatesheadCover design by Peter Cheseret

A catalogue record for this book is available from the British Library

Library of Congress Cataloging-in-Publication Data

Cities and climate change : global report on human settlements, 2011 / United Nations Human Settlements Programme.p. cm.

Includes bibliographical references and index.ISBN 978-1-84971-370-2 (hardback) — ISBN 978-1-84971-371-9 (pbk.) 1. Human beings—Effect of climate on. 2. Human settlements.

3. Urban climatology. 4. Climatic changes. I. United Nations Human Settlements Programme. GF71.C45 2011304.2'5—dc22

2010050454

At Earthscan we strive to minimize our environmental impacts and carbon footprint through reducing waste, recycling and offsetting our CO2emissions, including those created through publication of this book. For more details of our environmental policy, see www.earthscan.co.uk.

This book was printed in Malta by Gutenberg Press. The paper used is FSC certified and the inks are vegetable based.

FOREWORD

In the decades to come, climate change may make hundreds of millions of urban residents – and in particular the poorest andmost marginalized – increasingly vulnerable to floods, landslides, extreme weather events and other natural disasters. Citydwellers may also face reduced access to fresh water as a result of drought or the encroachment of saltwater on drinking watersupplies. These are the forecasts, based on the best available science. Yet none of these scenarios needs to occur, provided weact now with determination and solidarity.

This year’s edition of UN-Habitat’s Global Report on Human Settlements elucidates the relationship between urbansettlements and climate change, and suggests how cities and towns that have not yet adopted climate change policies can beginto do so. The report details the possible impacts of climate change on cities and towns. It also reviews mitigation and adapta-tion steps being taken by national and local authorities, and assesses their potential to shape future climate change policy.

Urban development has traditionally been seen as a national concern. This report shows its international relevance.Cities and towns contribute significantly to climate change – from the fossil fuels used for electricity generation, transport andindustrial production, to waste disposal and changes in land use.

I commend this report to all concerned with improving the ability of towns and cities to mitigate climate change andadapt to its impacts. How cities and towns are planned affects not just the health and well-being of their inhabitants, but theglobal environment and our prospects for sustainable development.

Ban Ki-moonSecretary-General

United Nations

INTRODUCTION

The effects of urbanization and climate change are converging in dangerous ways that seriously threaten the world’s environ-mental, economic and social stability. Cities and Climate Change: Global Report on Human Settlements 2011 seeks to improveknowledge, among governments and all those interested in urban development and in climate change, on the contribution ofcities to climate change, the impacts of climate change on cities, and how cities are mitigating and adapting to climate change.More importantly, the Report identifies promising mitigation and adaptation measures that are supportive of more sustainableand resilient urban development paths.

The Report argues that local action is indispensable for the realization of national climate change commitments agreedthrough international negotiations. Yet most of the mechanisms within the international climate change framework areaddressed primarily to national governments and do not indicate a clear process by which local governments, stakeholders andactors may participate. Despite these challenges, the current multilevel climate change framework does offer opportunities forlocal action at the city level. The crux of the challenge is that actors at all levels need to move within short time frames toguarantee long-term and wide-ranging global interests, which can seem remote and unpredictable at best.

An important finding of the Report is that the proportion of human-induced (or anthropogenic) greenhouse gas (GHG)emissions resulting from cities could be between 40 and 70 per cent, using production-based figures (i.e. figures calculated byadding up GHG emissions from entities located within cities). This is in comparison with as high as 60 to 70 per cent if aconsumption-based method is used (i.e. figures calculated by adding up GHG emissions resulting from the production of allgoods consumed by urban residents, irrespective of the geographic location of the production). The main sources of GHGemissions from urban areas are related to the consumption of fossil fuels. They include energy supply for electricity generation(mainly from coal, gas and oil); transportation; energy use in commercial and residential buildings for lighting, cooking, spaceheating, and cooling; industrial production; and waste.

However, the Report concludes that it is impossible to make accurate statements about the scale of urban emissions, asthere is no globally accepted method for determining their magnitude. In addition, the vast majority of the world’s urbancentres have not attempted to conduct GHG emission inventories.

The Report argues that, with increasing urbanization, understanding the impacts of climate change on the urbanenvironment will become even more important. Evidence is mounting that climate change presents unique challenges forurban areas and their growing populations. These impacts are a result of the following climatic changes:

• Warmer and more frequent hot days and nights over most land areas;• Fewer cold days and nights in many parts of the world;• Frequency increases in warm spells/heat waves over most land areas;• Increased frequency of heavy precipitation events over most areas;• Increase in areas affected by drought;• Increases in intense tropical cyclone activity in some parts of the world; and• Increased incidence of extreme high sea levels in some parts of the world.

Beyond the physical risks posed by the climatic changes above, some cities will face difficulties in providing basic services totheir inhabitants. These changes will affect water supply, physical infrastructure, transport, ecosystem goods and services,energy provision and industrial production. Local economies will be disrupted and populations will be stripped of their assetsand livelihoods.

The impacts of climate change will be particularly severe in low-elevation coastal zones, where many of the world’slargest cities are located. Although they account for only 2 per cent of the world’s total land area, approximately 13 per cent ofthe world’s urban population lives in these zones – with Asia having a higher concentration.

While local climate change risks, vulnerabilities and adaptive capacity vary across cities, evidence suggests some keycommon themes. First, climate change impacts may have ripple effects across many sectors of city life. Second, climate changedoes not impact everyone within a city in the same way: gender, age, race and wealth have implications for the vulnerability ofindividuals and groups. Third, in terms of urban planning, failure to adjust zoning and building codes and standards with an eyeto the future may limit the prospects of infrastructure adaptation and place lives and assets at risk. Fourth, climate changeimpacts can be long-lasting and can spread worldwide.

viiIntroduction

In proposing the way forward, following a global review of climate change mitigation and adaptation measures taken bycities all over the world, the Report emphasizes that several principles are fundamental to an integrated, multipartner approachtowards climate change action at the urban level:

• No single mitigation or adaptation policy is equally well-suited to all cities;• It would be beneficial to take an opportunity/risk management approach in a sustainable development perspective,

considering not only emissions, but also risks that are present in a range of possible climate and socioeconomic futures;• Policies should emphasize, encourage, and reward ‘synergies’ and ‘co-benefits’ (i.e. what policies can do to achieve both

developmental and climate change response goals);• Climate change policies should address both near-term and longer-term issues and needs; and• Policies should include new approaches that support multiscale and multisector action, rooted in the different expecta-

tions of a wide range of partners.

The Report suggests three main areas in which the international community can support and enable more effective urbanmitigation and adaptation responses:

• Financial resources need to be made more directly available to local players – for example, for climate change adaptationin vulnerable cities, for investment in a portfolio of alternative energy options, and in mitigation partnerships betweenlocal governments and local private sector organizations;

• Bureaucratic burdens on local access to international support should be eased, with the international community helpingto create direct communication and accountability channels between local actors and international donors; and

• Information on climate change science and options for mitigation and adaptation responses should be made more widelyavailable by the Intergovernmental Panel on Climate Change (IPCC), the United Nations and other international organiza-tions, including available knowledge on observed and future climate impacts on urban centres, on urban-based mitigationand adaptation alternatives, and on the costs, benefits, potentials and limits of these options.

With respect to the national level, the Report suggests that national governments should use the following mechanisms toenable mitigation and adaptation actions at the local level:

• Engage in the design and implementation of national mitigation strategies and adaptation planning;• Offer tax rebates, tax exceptions and other incentives for investments in alternative energy sources, energy-efficient

appliances, and climate-proof infrastructure, houses and appliances, among other climate change mitigation and adapta-tion actions;

• Encourage appropriate climate responses (for example, redesign policies enacted with other issues in mind or in periodsprior to climate change, such as flood protection policies that can result in maladaptations);

• Enhance coordination and streamlining between sectoral and administrative entities (for instance, make sure thatdecisions by one city to protect coastal areas with barriers do not have impacts on basins that are suppliers of fresh water,or wetland ecologies that are important to the economic base of that city or other cities inland);

• Develop partnerships with non-governmental actors to share risks (for example, national governments can work withprivate insurance providers to offer protection to each city without requiring each to make a sizeable investment in orderto reduce risks from a particular kind of low-probability threat); and

• Anticipate and plan for the possibility of much more substantial climate change impacts and adaptation needs in thelonger term than those that are currently anticipated in the next decades.

For the local level, the Report suggests, broadly, that urban policy-makers should begin from an awareness of local developmentaspirations and preferences, local knowledge of needs and options, local realities that shape choices, and local potential forinnovation. In this context, urban local authorities should:

• Develop a vision of where they want their future development to go and find ways to relate climate change responses tourban development aspirations;

• Expand the scope of community participation and action by representatives of the private sector, neighbourhoods(especially the poor) and grassroots groups, as well as opinion leaders of all kinds, in order to ensure a broad-based collec-tion of perspectives; and

• Using an inclusive, participatory process, cities should conduct vulnerability assessments to identify common and differ-entiated risks to their urban development plans and their different demographic sectors, and decide on objectives andways to reduce those risks.

To achieve more effective policies, local governments need to expand the scope, accountability and effectiveness of participa-tion and engagement with non-governmental organizations (NGOs), such as community and grassroots groups, the academicsector, the private sector and opinion leaders. Effective engagement with NGOs will serve multiple purposes:

• It will become a source of innovative options, as well as both scientific and locally relevant knowledge;• It will allow participants to understand and mediate the diverse perspectives and interests at play; and• It will provide broad-based support for decisions and promote knowledge on the causes of emissions and vulnerabilities,

as well as mitigation and adaptation options thus achieved.

Partnerships with the private sector and NGOs are of special relevance in this context. For example:

• Resources from international, national and local private organizations can be mobilized to invest in the development ofnew technologies, housing projects and climate-proof infrastructures, and to assist in the development of climate changerisk assessments; and

• The widespread involvement of NGOs in climate arenas as diverse as climate awareness and education and disaster reliefshould be welcomed – the inputs and perspectives of these organizations can be harnessed to help develop a moreintegrated urban development planning.

Finally, the Report suggests that broad-based oversight organizations, such as advisory boards, representing the interests of allactors, should be created to help avoid the danger that private or sectarian interests may distort local action (for instance, byinvesting in technologies, infrastructures and housing that only benefit a minority, or by hijacking the benefits of grassrootsfunding). This is especially of concern in urban areas within countries that have experienced strong centralized control in thehands of local elites and state agents, but the principle of broad-based oversight can and should be practised everywhere.

Many towns and cities, especially in developing countries, are still grappling with the challenges of how to put in placeclimate change strategies, how to access international climate change funding and how to learn from pioneering cities. Ibelieve this Global Report will provide a starting point for such towns and cities. More generally, I believe this Report willcontribute to raising global awareness of the important role that cities can and should play in the mitigation of greenhouse gasemissions and in adapting to climate change.

Dr Joan ClosUnder-Secretary-General and Executive Director

United Nations Human Settlements Programme (UN-Habitat)

viii Cities and Climate Change

ACKNOWLEDGEMENTS

MANAGEMENT TEAMDirector: Oyebanji O. Oyeyinka.Chief editor: Naison D. Mutizwa-Mangiza.

AUTHORS: UN-HABITAT CORE TEAMNaison D. Mutizwa-Mangiza; Ben C. Arimah; Inge Jensen; Edlam Abera Yemeru; Michael K. Kinyanjui.

AUTHORS: EXTERNAL CONSULTANTSPatricia Romero Lankao and Daniel M. Gnatz, Institute for the Study of Society and Environment, National Center forAtmospheric Research, Colorado, US (Chapters 1, 2 and 7); Sebastian Carney, Tyndall Centre for Climate Change Research,Manchester, UK (Chapter 2); Tom Wilbanks, Oak Ridge National Laboratory, Tennessee, US (Chapter 7); David Dodman, DavidSatterthwaite and Saleem Huq, International Institute for Environment and Development, UK (Chapters 3 and 6); MatthiasRuth, Rebecca Gasper and Andrew Blohm, University of Maryland, US (Chapter 4); Harriet Bulkeley and Vanesa Castán Broto,Durham University, UK, with the assistance of Andrea Armstrong, Anne Maassen and Tori Milledge (Chapter 5).

PREPARATION OF STATISTICAL ANNEX (UN-HABITAT)Gora Mboup; Inge Jensen; Ann Kibet; Michael K. Kinyanjui; Julius Majale; Philip Mukungu; Pius Muriithi; Wandia Riunga.

TECHNICAL SUPPORT TEAM (UN-HABITAT)Nelly Kan’gethe; Naomi Mutiso-Kyalo.

INTERNATIONAL ADVISERS (HS-NET ADVISORY BOARD MEMBERS)1

Samuel Babatunde Agbola, Department of Urban and Regional Planning, University of Ibadan, Nigeria; Louis Albrechts,Institute for Urban and Regional Planning, Catholic University of Leuven, Belgium; Suocheng Dong, Institute of GeographicSciences and Natural Resources Research, Chinese Academy of Sciences, China; Ingemar Elander, Centre for Urban andRegional Research, Örebro University, Sweden; József Hegedüs, Metropolitan Research Institute (Városkutatás Kft), Hungary;Alfonso Iracheta, Programme of Urban and Environmental Studies, El Colegio Mexiquense, Mexico; A. K. Jain, DelhiDevelopment Authority, India; Paula Jiron, Housing Institute, University of Chile, Chile; Winnie Mitullah, Institute ofDevelopment Studies (IDS), University of Nairobi, Kenya; Aloysius Mosha, Department of Architecture and Planning,University of Botswana, Botswana; Mee Kam Ng, Centre for Urban Planning and Environmental Management, University ofHong Kong; Deike Peters, Centre for Metropolitan Studies, Berlin University of Technology, Germany; Debra Roberts,eThekwini Municipality, Durban, South Africa; Pamela Robinson, School of Urban and Regional Planning, Ryerson University,Toronto, Canada; Elliott Sclar, Centre for Sustainable Urban Development, Columbia University, US; Dina K. Shehayeb,Housing and Building National Research Centre, Egypt; Graham Tipple, School of Architecture, Planning and Landscape,Newcastle University, UK; Iván Tosics, Metropolitan Research Institute (Városkutatás Kft), Budapest, Hungary; Belinda Yuen,School of Design and Environment, National University of Singapore, Singapore.

OTHER INTERNATIONAL ADVISERSTitilope Ngozi Akosa, Centre for 21st Century Issues, Lagos, Nigeria; Gotelind Alber, Sustainable Energy and Climate PolicyConsultant, Berlin, Germany; Margaret Alston, Department of Social Work, Monash University, Australia; Jenny Crawford,Royal Town Planning Institute, UK; Simin Davoudi, Institute for Research on Environment and Sustainability, NewcastleUniversity, UK; Harry Dimitriou, Bartlett School of Planning, University College London, UK; Will French, Royal Town PlanningInstitute, UK; Rose Gilroy, Institute for Policy and Planning, Newcastle University, UK; Zan Gunn, School of Architecture,Planning and Landscape, Newcastle University, UK; Cliff Hague, Commonwealth Association of Planners, UK; Collin Haylock,Ryder HKS, UK; Patsy Healey, School of Architecture, Planning and Landscape, Newcastle University, UK; Jean Hillier, GlobalUrban Research Centre, Newcastle University, UK; Aira Marjatta Kalela, Ministry for Foreign Affairs, Finland; Prabha Kholsa,VisAble Data, Burnaby, Canada; Nina Laurie, School of Geography, Politics and Sociology, Newcastle University, UK; AliMadanjpour, Global Urban Research Centre, Newcastle University, UK; Michael Majale, School of Architecture, Planning andLandscape, Newcastle University, UK; Peter Newman, Sustainability Policy Institute, Curtin University, Australia; Ambe Njoh,College of Arts and Sciences, University of South Florida, US; John Pendlebury, Global Urban Research Centre, NewcastleUniversity, UK; Christine Platt, Commonwealth Association of Planners, South Africa; Carole Rakodi, Religions andDevelopment Research Programme, University of Birmingham, UK; Diana Reckien, Potsdam Institute for Climate ImpactResearch, Germany; Maggie Roe, Institute for Policy Practice, Newcastle University, UK; Christopher Rodgers, Newcastle LawSchool, Newcastle University, UK; Mark Seasons, School of Planning, University of Waterloo, Ontario, Canada; Bruce Stiftel,Georgia Institute of Technology, US; Pablo Suarez, Red Cross/Red Crescent Climate Centre, Boston University, US; AlisonTodes, School of Architecture and Planning, University of the Witwatersrand, WITS University, South Africa; Robert Upton,Royal Town Planning Institute, UK; Geoff Vigar, School of Architecture, Planning and Landscape, Newcastle University, UK;Vanessa Watson, School of Architecture, Planning and Geomatics, University of Cape Town, South Africa.

ADVISERS (UN-HABITAT)Sharif Ahmed; Karin Buhren, Maharufa Hossain; Robert Kehew, Cecilia Kinuthia-Njenga; Lucia Kiwala, Rachael M’Rabu; RafTuts; Xing Quan Zhang.

AUTHORS OF BACKGROUND PAPERSStephen A. Hammer and Lily Parshall, Center for Energy, Marine Transportation and Public Policy (CEMTPP), ColumbiaUniversity, US; Cynthia Rosenzweig and Masahiko Haraguchi, Climate Impacts Group, NASA Goddard Institute for SpaceStudies, US (‘The contribution of urban areas to climate change: New York City case study’). Carolina Burle Schmidt Dubeuxand Emilio Lèbre La Rovere, Center for Integrated Studies on Climate Change and the Environment, Centro Clima, Brazil (‘Thecontribution of urban areas to climate change: The case study of São Paulo, Brazil’). David Dodman, International Institute forEnvironment and Development, UK; Euster Kibona and Linda Kiluma, Environmental Protection and Management Services,Dar es Salaam, Tanzania (‘Tomorrow is too late: Responding to social and climate vulnerability in Dar es Salaam, Tanzania’).Jimin Zhao, Environmental Change Institute, University of Oxford, UK (‘Climate change mitigation in Beijing, China’). HeikeSchroeder, Tyndall Centre for Climate Change Research and the James Martin 21st Century School, Environmental ChangeInstitute, University of Oxford, UK (‘Climate change mitigation in Los Angeles, US’). David Rain, Environmental Studies,George Washington University, US; Ryan Engstrom, Spatial Analysis Lab and Center for Urban Environmental Research, GeorgeWashington University, US; Christianna Ludlow, independent researcher, US; and Sarah Antos, World Health Organization(‘Accra, Ghana: A city vulnerable to flooding and drought-induced migration’). María Eugenia Ibarrarán, Department ofEconomics and Business, Universidad Iberoamericana Puebla, Mexico (‘Climate’s long-term impacts on Mexico City’s urbaninfrastructure’). Rebecca Gasper and Andrew Blohm, Center for Integrative Environmental Research, University of Maryland,US (‘Climate change in Hamilton City, New Zealand: Sectoral impacts and governmental response’). Alex Aylett, InternationalCenter for Sustainable Cities, Canada (‘Changing perceptions of climate mitigation among competing priorities: The case ofDurban, South Africa’). Alex Nickson, Greater London Authority, UK (‘Cities and climate change: Adaptation in London, UK’).Gotelind Alber, independent consultant, Germany (‘Gender, cities and climate change’).

PUBLISHING TEAM (EARTHSCAN LTD)Jonathan Sinclair Wilson; Hamish Ironside; Alison Kuznets; Andrea Service.

x Cities and Climate Change

1 The HS-Net Advisory Board consists of experienced researchers in the human settlements field, selected to represent the various geographical regionsof the world. The primary role of the advisory board is to advise UN-Habitat on the substantive content and organization of the Global Report onHuman Settlements.

NOTE

CONTENTS

Foreword vIntroduction viAcknowledgements ixList of Figures, Boxes and Tables xvList of Acronyms and Abbreviations xviii

1 Urbanization and the Challenge of Climate Change 1Urbanization and Climate Change 2Evidence of Climate Change: Implications for Urban Centres 4

How the climate system functions and what is changing 4The types of greenhouse gases 6The causes of climate change 9

Framework for Exploring the Linkages between Urban Areas and Climate Change 10Drivers of urban contributions to GHG emissions 10Urban vulnerability and ‘resilience’ 12

Concluding Remarks and Structure of the Global Report 14Notes 16

2 Cities and the International Climate Change Framework 17The United Nations Framework Convention on Climate Change 17The Kyoto Protocol 20Other Climate Change Arrangements 21

International level 21National level 24State/provincial level 25Local/city level 25

The Potential of the International Climate Change Framework for Local Action 28Concluding Remarks 30Notes 31

3 The Contribution of Urban Areas to Climate Change 33Measuring Greenhouse Gas Emissions 33

International protocols for measuring greenhouse gas emissions 34Protocols for measuring corporate greenhouse gas emissions 34Protocols for measuring local government greenhouse gas emissions 35New baseline inventories for urban emissions 36Boundary issues 36

The Sources of Greenhouse Gas Emissions 36Energy supply for electricity generation 38Transport 40Commercial and residential buildings 42Industry 43Waste 44Agriculture, land-use change and forestry 44

The Scale of Urban Emissions 45Global patterns of emissions 45Urban emissions in developed countries 46Urban emissions in developing countries 48Estimating the global-level urban emissions 51

Factors Influencing Emissions 52Geographic situation 52Demographic situation 53Urban form and density 54The urban economy 56The politics of measuring emissions 57

Concluding Remarks and Lessons for Policy 61Notes 62

4 The Impacts of Climate Change upon Urban Areas 65Climate Change Risks Facing Urban Areas 65

Sea-level rise 65Tropical cyclones 67Heavy precipitation events 67Extreme heat events 69Drought 70

Impacts upon Physical Infrastructure 70Residential and commercial structures 70Transportation systems 71Energy systems 72Water and sanitation systems 73

Economic Impacts 73Sectoral economic impacts 74Ecosystem services 77Livelihood impacts 77

Public Health Impacts 78Social Impacts 79

Poverty 79Gender 81Age 82Ethnic and other minorities (including indigenous groups) 83

Displacement and Forced Migration 84Identifying Cities Vulnerable to Climate Change 85

Urbanization 85Economic development 86Physical exposure 86Urban governance and planning 87Disaster preparedness 87

Concluding Remarks and Lessons for Policy 88Notes 89

5 Climate Change Mitigation Responses in Urban Areas 91Responses to Climate Change Mitigation in Urban Areas 92

Municipal policy approaches 93Urban development and design 94Built environment 95Urban infrastructure 98Transport 100Carbon sequestration 103Assessing the impact of urban climate change mitigation initiatives 105

Urban Governance for Climate Change Mitigation 107Modes of governing climate change mitigation 107Municipal governance 108

xii Cities and Climate Change

Modes of public–private collaboration in urban climate governance 112Opportunities and Constraints 115

Institutional factors shaping urban governance capacity 115Technical, material and financial factors shaping urban governance capacity 117Political factors shaping urban governance capacity 120

Comparative Analysis 123Concluding Remarks and Lessons for Policy 125Notes 126

6 Climate Change Adaptation Responses in Urban Areas 129Understanding Adaptation 129Household and Community Responses to the Impacts of Climate Change 131

Household responses 131Community responses 133

Local Government Responses to the Impacts of Climate Change 137National frameworks that support adaptation in urban areas 137Local government responses in developing countries 138Local government responses in developed countries 142The links between adaptation and disaster preparedness 144

Towards Effective City-Based Climate Change Adaptation Strategies 145Generic lessons for city governments 146Adaptation responses to potential impacts in different economic sectors 148Building resilience 149Adaptation planning and local governance 150UN-Habitat’s Cities and Climate Change Initiative 152

Financing Adaptation 153The costs of adaptation 154The infrastructure deficit 156The cost of addressing the infrastructure deficit 157

Challenges to Adaptation 157Concluding Remarks and Lessons for Policy 159Notes 160

7 Conclusion and Policy Directions 163Key Findings and Their Implications 164

Main issues of concern 164Cities and the multifaceted nature of climate responses 166Sources and drivers of cities’ GHG emissions 168The multiple urban faces of climate impacts and vulnerabilities 169Mitigation responses 170Adaptation responses 172

Addressing Urban GHG Emissions and Vulnerabilities: Challenges, Constraints and Opportunities 173Adaptation and Mitigation: Relationships with Urban Development and Policy 176

Climate change mitigation and urban development 176Climate change adaptation and urban development 177Mitigation and adaptation: Seeking synergies rather than conflicts 178

Future Policy Directions 179Principles for policy development 179International policies 180National policies 180City policies 181Policies of other partners in a global policy response 182

Concluding Remarks 183Notes 183

xiiiContents

STATISTICAL ANNEXTechnical Notes 187

Explanation of Symbols 187Country Groupings and Statistical Aggregates 187

World major groupings 187Countries in the Human Development Index aggregates 187Countries in the income aggregates 188Sub-regional aggregates 188

Nomenclature and Order of Presentation 189Definition of Terms 189Sources of Data 191Notes 192

Data Tables 193Regional Aggregates 193

A.1 Total Population Size, Rate of Change and Population Density 193A.2 Urban and Rural Population Size and Rate of Change 194A.3 Urbanization 195A.4 Urban Agglomerations 196

Country-Level Data 199B.1 Total Population Size, Rate of Change and Population Density 199B.2 Urban and Rural Population Size and Rate of Change 203B.3 Urbanization and Urban Slum Dwellers 207B.4 Access to Drinking Water and Sanitation 211B.5 Poverty and Inequality 215B.6 Transport Infrastructure 219B.7 Greenhouse Gas Emissions and Rate of Change 223B.8 Greenhouse Gas Emissions per Capita and as a Proportion of World Total 227

City-Level Data 231C.1 Urban Agglomerations with 750,000 Inhabitants or More: Population Size and Rate of Change 231C.1 Population of Capital Cities (2009) 239C.1 Access to Services in Selected Cities 243

References 249Index 271

xiv Cities and Climate Change

LIST OF FIGURES, BOXES AND TABLES

FIGURES1.1 Cities in relation to current climate-related hazards 41.2 Schematic diagram of the greenhouse effect 61.3 Global and continental temperature change 71.4 Global anthropogenic GHG emissions 81.5 Relationships between urbanization levels and CO2 emissions per capita 91.6 Carbon intensity and economic development (2003) 93.1 Global GHG emissions by sector and end use/activity 383.2 World electricity generation by fuel type (1971–2008) 383.3 CO2 emissions per capita in selected countries and world regions (2007) 453.4 GHG emissions inventory, New York City, US 474.1 Relationship between CO2 emissions reduction, temperature stabilization and sea-level rise 674.2 World population and recorded natural and technological disasters (e.g. industrial and transport accidents)

(1950–2005) 885.1 The ‘low hanging fruits’ of urban GHG mitigation 1056.1 The main stages of city-based climate change adaptation 1386.2 Process for developing a municipal adaptation plan in Cape Town, South Africa 1426.3 Adapting infrastructure to sea-level rise 1496.4 Adaptation costs, avoided damages and residual damage 156

BOXES1.1 Climate change-related terminology 51.2 Recent changes in climate of relevance to urban areas 61.3 Mexico City: Environmental degradation and vulnerability 121.4 Capacity to learn and adapt in Bangladesh 132.1 The Intergovernmental Panel on Climate Change 182.2 Funding mechanisms of the UNFCCC 192.3 Flexible mechanisms under the Kyoto Protocol 202.4 UN-Habitat’s Cities and Climate Change Initiative 222.5 International Standard for Determining Greenhouse Gas Emissions for Cities 232.6 Climate change initiatives at the World Bank 232.7 Major international city networks and initiatives on climate change 262.8 Non-governmental constituencies of the UNFCCC 273.1 The contribution of transportation to GHG emissions in Bangkok, Thailand 413.2 Contribution to GHG emissions, New York City, US 473.3 Contribution to GHG emissions, São Paulo, Brazil 493.4 GHG emissions and climate change in Mexico City 503.5 Contribution to GHG emissions, Cape Town, South Africa 504.1 Increased incidence of flash flooding in Mexico City 684.2 Extreme heat event trends in the US and Europe 694.3 Global changes in energy demand 724.4 Cross-sectoral impacts of tropical cyclones: The case of Dhaka, Bangladesh 74

4.5 Economic impacts of Hurricane Katrina, US 754.6 Climate change impacts upon the tourism industry 754.7 Impacts of climate change upon the insurance industry 764.8 Poverty and climate change impacts in cities 804.9 Climate change risks for children 834.10 Vulnerability of slums to climate change: The case of Kampala, Uganda 875.1 Strategic approaches to urban climate change policy: The CCP Milestone Methodology 935.2 Strategic approaches to urban climate change policy: The Climate Alliance’s Climate Compass 935.3 Urban development challenges for mitigating climate change: Thailand and Canada 945.4 Sustainable living and brownfield development, Stockholm, Sweden 955.5 Retrofitting domestic, public and commercial buildings in the UK and the US 965.6 Sustainable and affordable houses for the poor in Bishnek, Kyrgyzstan 975.7 Feminist action to gain recognition for women waste pickers in Mumbai, India 995.8 Raising public awareness for waste reduction in Yokohama, Japan 1005.9 Congestion charges: Past, present and future 1015.10 The future of energy? Piloting urban carbon capture and storage in Rotterdam, The Netherlands 1045.11 Planning for a Garden City in Singapore 1045.12 The Green Lighting Programme in Beijing, China 1095.13 Provision of energy in Los Angeles, US 1105.14 Low-energy and passive housing in Ljubljana, Slovenia 1105.15 Manchester Is My Planet: Mobilizing the community? 1145.16 Climate change mitigation initiatives developed by international city networks 1145.17 Distribution of resources for climate change mitigation in Mexico City 1195.18 Political leadership models in Los Angeles, US 1215.19 Trigger events in Beijing, China 1215.20 Obstacles to climate change mitigation actions in Durban, South Africa 1246.1 Household and community responses to flooding in informal settlements in Lagos, Nigeria 1326.2 Household responses to reducing risks from flooding in Korail, Bangladesh 1336.3 Risk reduction by the Homeless People’s Federation of the Philippines 1356.4 The scale of adaptation deficit in selected cities 1396.5 Key risks identified by the climate change adaptation strategy of London, UK 1436.6 Citizen-driven city adaptation in Tatabánya, Hungary 1517.1 Key principles for urban climate change policy development: The international community 1807.2 Key principles for urban climate change policy development: National governments 1817.3 Key principles for urban climate change policy development: Local authorities 1827.4 Key principles for urban climate change policy development: Other partners 182

TABLES1.1 Urban population projections, by region (2010–2030) 31.2 Urban population in different ‘ecozones’, by region (2000 and 2025) 41.3 Major characteristics of the most important GHGs 71.4 Total and per capita GHG emissions (‘top 20 countries’) 82.1 Major milestones in international climate change governance 182.2 Focus areas for a coordinated United Nations response to climate change 223.1 Sectors assessed for national GHG inventories 343.2 Emissions scopes for companies 353.3 ICLEI categorization of community sectors 353.4 Emissions scopes for local authorities 363.5 Representative GHG baselines for selected cities and countries 373.6 Electricity generation by energy source 393.7 Categories of renewable energy technologies 393.8 Private passenger transport energy use, urban density and GHG emissions, selected cities 403.9 Ground transportation, fuel consumption and GHG emissions, selected cities 413.10 Energy consumption by income level and dwelling size in the US (2008) 433.11 Comparisons of city and national GHG emissions, selected cities 463.12 GHG emissions inventories, selected cities 463.13 CO2 emissions from South African urban areas (2004) 503.14 Cities’ contribution to global anthropogenic GHG emissions, by sector 51

xvi Cities and Climate Change

3.15 The contribution of urban areas to various aspects of climate change 523.16 CO2 emissions, population growth and national income 533.17 Average population density of cities’ built-up areas 543.18 Urban GHG emissions: Production versus consumption perspectives 604.1 Projected impacts upon urban areas of changes in extreme weather and climate events 664.2 Exposure to floods in cities 714.3 Impacts of urbanization upon ecosystem services 774.4 Gender and climate vulnerability 815.1 Cities and the mitigation of climate change 915.2 Typology of policy response to climate mitigation in the urban arena 935.3 Climate change mitigation through urban development and design 955.4 Climate change mitigation in the built environment 965.5 Costs and benefits of a project to install 200,000 solar water heaters in the residential sector in Yinzhou, China 975.6 Climate change mitigation and urban infrastructures 985.7 Climate change mitigation and transportation 1015.8 Bus rapid transit (BRT) systems planned or in operation in different regions 1025.9 Climate change mitigation and carbon sequestration 1035.10 Identifying and prioritizing climate change mitigation actions 1065.11 Mitigating urban GHG emissions: Production versus consumption perspectives 1065.12 Municipal modes of governing climate change 1085.13 Public–private modes of governing climate change 1125.14 Opportunities and constraints for governing climate change mitigation in the city 1156.1 Examples of asset-based actions at different levels to build resilience to extreme weather 1366.2 Adaptation measures for Bangkok, Thailand 1406.3 Ecosystem services provided by green spaces and street trees, London, UK 1436.4 Key risks and adaptation strategies in Melbourne, Australia 1446.5 Examples of climate change preparedness goals and actions 1466.6 Examples of specific adaptation interventions by sector 1486.7 Adaptation to extreme weather: The role of city/municipal governments 1526.8 Proposed and planned activities in the pilot cities of the Cities and Climate Change Initiative 1536.9 Annual investment needs by 2030 to cover climate change adaptation costs (estimates) 155

xviiList of Figures, Boxes and Tables

LIST OF ACRONYMS ANDABBREVIATIONS

°C degrees CelsiusBRT bus rapid transitC40 Cities Climate Leadership GroupCCCI Cities and Climate Change Initiative (UN-Habitat)CCP Cities for Climate Protection Campaign (ICLEI)CDM Clean Development Mechanismcm centimetreCO2 carbon dioxideCO2eq carbon dioxide equivalentConvention, the United Nations Framework Convention on Climate ChangeCOP Conference of the Parties (to the UNFCCC)EU European UnionGDP gross domestic productGEF Global Environment FacilityGHG greenhouse gasha hectareICLEI Local Governments for Sustainability IPCC Intergovernmental Panel on Climate ChangekW kilowattkWh kilowatt hourkm kilometrem metremm millimetreMW megawatt (1MW = 1000kW)MWh megawatt hour (1MWh = 1000kWh)NAPA National Adaptation Programme of ActionNGO non-governmental organizationOECD Organisation for Economic Co-operation and DevelopmentRMB Chinese yuanTWh terawatt hour (1TWh = 1 million MWh)UCLG United Cities and Local GovernmentsUK United Kingdom of Great Britain and Northern IrelandUN United NationsUNDP United Nations Development ProgrammeUNEP United Nations Environment ProgrammeUNFCCC United Nations Framework Convention on Climate ChangeUN-Habitat United Nations Human Settlements ProgrammeUS United States WMO World Meteorological Organization

As the world enters the second decade in the new millen-nium, humanity faces a very dangerous threat. Fuelled bytwo powerful human-induced forces that have beenunleashed by development and manipulation of the environ-ment in the industrial age, the effects of urbanization andclimate change are converging in dangerous ways whichthreaten to have unprecedented negative impacts uponquality of life, and economic and social stability.

Alongside the threats posed by the convergence ofthe effects of urbanization and climate change, however, isan equally compelling set of opportunities. Urban areas, withtheir high concentration of population, industries and infra-structure, are likely to face the most severe impacts ofclimate change. The same concentration of people, industrialand cultural activities, however, will make them crucibles ofinnovation, where strategies can be catalysed to promotereductions in greenhouse gas (GHG) emissions (mitigation)and to improve coping mechanisms, disaster warningsystems, and social and economic equity, to reduce vulnera-bility to climate change impacts (adaptation).

While some cities are shrinking, many urban centresare seeing rapid and largely uncontrolled population growth,creating a pattern of rapid urbanization. Most of this growthis now taking place in developing countries1 and is concen-trated in informal settlements and slum areas. Therefore,the very urban areas that are growing fastest are also thosethat are least equipped to deal with the threat of climatechange, as well as other environmental and socio-economicchallenges. These areas often have profound deficits ingovernance, infrastructure, and economic and social equity.

People arriving in already overstressed urban centresare forced to live in dangerous areas that are unsuitable forreal estate or industrial development, many constructingtheir own homes in informal settlements on floodplains, inswamp areas and on unstable hillsides, often with inade-quate or completely lacking infrastructure and basic servicesto support human life, safety and development. Many ofthese slum residents are often blamed by their governmentsfor their own poor living conditions. Even without additionalweather-related stresses, such as higher-intensity or morefrequent storms, these are dangerous living environments.

Climate change, the second major force unleashed byhuman industrial development, is quickly building momen-

tum. Climate change is increasing the magnitude of many ofthe threats to urban areas that are already being experiencedas a result of rapid urbanization. Yet, climate change can alsobe a source of opportunities to redirect the patterns ofproduction and consumption of cities and individuals, at thesame time enhancing their capacity to cope with hazards.

Climate change is an outcome of human-induceddriving forces such as the combustion of fossil fuels and land-use changes, but with wide-ranging consequences for theplanet and for human settlements all over the world. Therange of effects include a warming of sea water, and itsconsequent expansion, that has provided some warningsigns, including the collapse of the ice shelves such as LarsenA (1995) and Larsen B (2002) in Antarctica. This meltingpolar ice threatens to add more water to the already expand-ing warmer seas, accelerating a dangerous sea-level rise thatthreatens many coastal urban centres. At the same time, theincreasingly warm (and acidic2) seas threaten, along withpollution and other anthropogenic or human-related drivers,the very existence of coral reef ecosystems around theworld, giving rise to new risks in urban coastal areas thatgain protection from the ecosystem services of coral reefsand other aquatic ecosystems. These changes to the naturalworld gravely threaten the health and quality of life of manyurban dwellers.

With sea-level rise, urban areas along the coasts,particularly those in low-elevation coastal zones,3 will bethreatened with inundation and flooding, saltwater intrusionaffecting drinking water supplies, increased coastal erosionand reductions in liveable land space. All of these effects,however, will be compounded by other climate impacts,including increase in the duration and intensity of stormssuch as hurricanes and cyclones, creating extreme hazardsfor both rich and poor populations occupying low-elevationcoastal zones.

Even in non-coastal areas, the convergence of rapidurbanization with climate change can be very dangerous.Poor people living on unstable hillsides could face continu-ous threats of being swept away or buried by rain-inducedmud- and rock-slides. Uncontrolled growth of urban centresinto natural forest or brush areas that will dry out withincreases in temperatures and in the intensity and durationof droughts will see increases in the frequency of life- and

C H A P T E R

URBANIZATION AND THECHALLENGE OF CLIMATE CHANGE

1

The effects of urbanization andclimate change …threaten to haveunprecedentednegative impactsupon quality of life,and economic andsocial stability

Climate change canalso be a source ofopportunities toredirect the patternsof production andconsumption ofcities and individuals

property-threatening wildfires. Droughts in both coastal andnon-coastal cities could disrupt urban water supplies andsupplies of forest and agricultural products. These impactswill fall disproportionately upon the urban poor in develop-ing as well as developed countries.

In developed countries, an uneven distribution ofpolitical and economic power is the reason why the poor,ethnic and other minorities, and women will bear the bruntof climate change. This uneven distribution of vulnerabilitycan have a destabilizing effect within these countries. Thiscan be seen, for instance, in the racial and social tension thatcame to the fore in the US when it became evident thatAfrican-Americans, the poor and the elderly were dispropor-tionately affected by Hurricane Katrina in 2005.

It is true that destruction of property and loss of lifein the coastal areas and elsewhere will certainly not belimited to the poor; but it is also true that affluent segmentsof the population will be much better protected by insur-ance, political and economic advantages. It is, however,highly probable that the need for responses to an increasedfrequency of disasters will stress national economies even indeveloped countries, also creating much higher stress on theglobal economy.

The challenges associated with the rapid pace ofurbanization will complicate responses to climate change.The other side of the coin, however, is that urbanization willalso offer many opportunities to develop cohesive responsesin both mitigation and adaptation strategies to deal withclimate change. The populations, enterprises and authoritiesof urban centres will be fundamental players in developingthese strategies. In this way, climate change itself will offeropportunities, or it will force cities and humanity, in general,to improve global, national and urban governance to fosterthe realization of human dignity, economic and social justice,as well as sustainable development.

The purpose of this chapter is to identify the mainissues of concern as they relate to urban areas and climatechange. It describes, in the section below, key urbanizationtrends as they relate to climate change, and presents thereasons why it is important to explore the factors shapingurban development and changes in the Earth’s climatesystem. The section after that presents, in summary form,the most important and recent evidence of the causes ofclimate change, and briefly looks at climate change implica-tions for urban centres. This is followed by a presentation ofthe framework for exploring linkages between urban areasand climate change used in this Global Report, covering twomain issues: drivers of urban contributions to climatechange; and urban vulnerability and resilience. The finalsection contains some concluding remarks and a shortdescription of the main contents of the rest of the report.

URBANIZATION ANDCLIMATE CHANGEDevelopment and its many environmental impacts areinextricably bound. As such, urbanization and climatechange are co-evolving in such a way that populations, often

in densely packed urban areas, will be placed at much higherrisk from climate change as well as from other profoundsocietal and environmental changes. The pace of thesechanges is rapid, and for this reason, many aspects of urbanchange during recent decades are of importance for thisGlobal Report. There are six primary reasons why it is impor-tant to understand the forces shaping the world’s growingurban areas in order to be able to mitigate climate changeand to cope with its inevitable consequences. First amongthese is the rapid pace of urban population growth. By theend of the last decade the world reached a milestone when,for the first time in human history, half of the world’spopulation lived in urban areas. The pace of urbanization inthe world today is unprecedented, with a near quintupling ofthe urban population between 1950 and 2011.4

The second important issue bearing on urbanizationand climate change is that, unlike urbanization during theearly 20th century, which was mostly confined to developedcountries, the fastest rates of urbanization are currentlytaking place in the least developed countries, followed bythe rest of the developing countries (see Table 1.1), whichnow host nearly three-quarters of the world’s urban popula-tion. In fact, more than 90 per cent of the world’s urbanpopulation growth is currently taking place in developingcountries.5 This rapid urbanization of developing countries,coupled with the increased intensity and frequency ofadverse weather events, will have devastating effects onthese countries, which also have lower capacities to dealwith the consequences of climate change.6

Third, while the populations of some cities are shrink-ing, the number of large cities and the size of the world’slargest cities are increasing. The number of cities in theworld with populations greater than 1 million increased from75 in 1950 to 447 in 2011; while during the same period,the average size of the world’s 100 largest cities increasedfrom 2.0 to 7.6 million. By 2020, it is projected that therewill be 527 cities with a population of more than 1 million,while the average size of the world’s 100 largest cities willhave reached 8.5 million.7 However, it is significant that thebulk of new urban growth is taking place in smaller urbanareas. For instance, urban centres with fewer than 500,000people are currently home to just over 50 per cent of thetotal urban population.8 The primary disadvantage of thisdevelopment pattern is that these smaller urban areas areoften institutionally weak and unable to promote effectivemitigation and adaptation actions. However, there is a possi-ble advantage to be gained here also, as the burgeoningdevelopment of these centres may be redirected in ways thatreduce their emission levels to a desired minimum (e.g.through the promotion of mono-centric urban structuresbased on the use of public transportation), and theirresilience and ability to cope with climate hazards and otherstresses enhanced (e.g. through the development of climate-proof urban infrastructure and effective response systems).

Fourth, since urban enterprises, vehicles and popula-tions are key sources of GHGs, gaining an understanding ofthe dynamics of the forces and systems that drive the urbangeneration of GHGs is fundamental in helping urban policy-makers, enterprises and consumers target the readily

An uneven distribution of political andeconomic power isthe reason why thepoor, ethnic andother minorities,and women willbear the brunt ofclimate change

Urbanization willalso offer manyopportunities todevelop cohesiveresponses in bothmitigation andadaptation strategiesto deal with climatechange

Urbanization andclimate change areco-evolving in such away thatpopulations, often indensely packedurban areas, will beplaced at muchhigher risk fromclimate change

2 Cities and Climate Change

available options to reduce those emissions at the same timethat urban resilience to the impacts of climate change isenhanced. For instance, many cities exceed the recom-mended annual average figure of 2.2 tonnes of CO2equivalent value (CO2eq) per capita.9

Fifth, cities are also centres of diverse kinds of innova-tions that may contribute to reducing or mitigatingemissions, adapting to climate change, and enhancingsustainability and resilience. Mechanisms for that purposeinclude changes in transportation, land-use patterns, and theproduction and consumption patterns of urban residents.The economies of scale, as well as proximity and concentra-tion of enterprises in cities, make it cheaper and easier totake the actions and provide the services necessary tominimize both emissions and climate hazards.10

Last, but certainly not least in importance, the dynam-ics of urban centres are intimately linked to geography.Latitude determines a city’s need for more or less energy torun air-conditioning and heating systems within its build-ings, industries and houses. However, cities also depend onbiodiversity, clean water and other ecosystem services thatthey have developed over existing ecosystems or ‘ecozones’,such as coastal areas, wetlands and drylands.11 Indeed,settling along large bodies of water such as seas, lakes andrivers has historically been a vital factor in the economic anddemographic growth of cities, and this trend continuestoday. For instance, ecozones near water bodies (inland andcoastal) have greater shares of population residing in urbanareas than other ecozones (see Table 1.2). In developingcountries especially, these urban centres are already facedwith flooding resulting from a combination of factors (suchas impermeable surfaces in the built environment, scarcity ofgreen spaces to absorb water flows and inadequate drainagesystems). There are also health-related risks that affectecozones near water bodies. These include flood-relatedincreases in diarrhoeal diseases, typhoid and cholera.

Many weather-related risks – which, as can be seen inFigure 1.1, already have an urban face – will be exacerbatedas climate change progresses and hazards such as sea-levelrise, saltwater intrusion and more intense storms becomeday-to-day realities for the poor and vulnerable populationsthat inhabit many of the most hazardous areas in urbancentres. Drylands are also home to a considerable share ofurban populations and, as will be illustrated later, these areastoo will see an increase in climate-related impacts, especiallyin the western parts of the US, the northeast of Brazil andaround the Mediterranean (see Table 1.2).

As illustrated in Figure 1.1, many urban dwellers andtheir livelihoods, property, quality of life and future prosper-ity are threatened by the risks from cyclones, flooding,landslides and drought: adverse events which climate changeis expected to aggravate. Yet, urbanization is not only asource of risks. Certain patterns of urban development canincrease resilience. For instance, while large populationdensities in urban areas create increased vulnerability, theyalso create the potential for city-scale changes in behaviourthat can mitigate human contributions to climate change andencourage adaptation to the inevitable changes that climatechange will bring. Furthermore, infrastructure developmentscan provide physical protection. As illustrated by Cuba’sexperience, well-designed communications and earlywarning systems can help to evacuate people swiftly whentropical storms approach.12 Appropriate urban planning canhelp to restrict growth of population and activities in risk-prone areas.

Given the above, it is necessary to pay attention tothe worsening global problem of climate change in relationto urban centres – the most local of the human systems onEarth – which concentrate more than half of the world’spopulation and have significant potential to perform keyroles in the climate change arena.

Many weather-related risks … willbe exacerbated asclimate changeprogresses andhazards such as sea-level rise,saltwater intrusionand more intensestorms become day-to-day realities

Appropriate urbanplanning can help torestrict growth ofpopulation and activities in risk-prone areas

3Urbanization and the Challenge of Climate Change

Urban populationprojections, by region(2010–2030)

Table 1.1Region Urban population Proportion of total population Urban population rate of

(millions) living in urban areas (%) change (% change per year)2010 2020 2030 2010 2020 2030 2010–2020 2020–2030

World total 3486 4176 4900 50.5 54.4 59.0 1.81 1.60Developed countries 930 988 1037 75.2 77.9 80.9 0.61 0.48North America 289 324 355 82.1 84.6 86.7 1.16 0.92Europe 533 552 567 72.8 75.4 78.4 0.35 0.27Other developed countries 108 111 114 70.5 73.3 76.8 0.33 0.20

Developing countries 2556 3188 3863 45.1 49.8 55.0 2.21 1.92Africa 413 569 761 40.0 44.6 49.9 3.21 2.91Sub-Saharan Africa 321 457 627 37.2 42.2 47.9 3.51 3.17Rest of Africa 92 113 135 54.0 57.6 62.2 2.06 1.79

Asia/Pacific 1675 2086 2517 41.4 46.5 52.3 2.20 1.88China 636 787 905 47.0 55.0 61.9 2.13 1.41India 364 463 590 30.0 33.9 39.7 2.40 2.42Rest of Asia/Pacific 674 836 1021 45.5 49.6 54.7 2.14 2.00

Latin America and the Caribbean 469 533 585 79.6 82.6 84.9 1.29 0.94Least developed countries 249 366 520 29.2 34.5 40.8 3.84 3.50Other developing countries 2307 2822 3344 47.9 52.8 58.1 2.01 1.70

Source: UN, 2010; see also Statistical Annex, Tables A.1, A.2, A.3, B.1, B.2, B.3

EVIDENCE OF CLIMATECHANGE: IMPLICATIONSFOR URBAN CENTRESThis section presents a brief overview of how the globalclimate system functions, and what is changing as a result ofclimate change. It also presents a brief summary of thecharacteristics of the main causes of climate change (i.e. theGHGs). The last part of this section takes a closer look at themain human activities that cause increasing GHG emissions.

How the climate system functions and what is changing

Several factors influence the climate of the Earth: the incom-ing energy from the Sun, the outgoing or radiated energyleaving the Earth, and the exchanges of energy amongoceans, land, atmosphere, ice and living organisms (seeFigure 1.2). Structure and dynamics within both the carboncycle (see Box 1.1) and the atmosphere can be equallyresponsible for alterations in climate. Within the atmos-

phere, incoming solar radiation and outgoing infrared radia-tion are affected by some gases and aerosols (see Box 1.1).While most aerosols have some cooling effect, the amount ofGHGs present in the Earth’s atmosphere before humanbeings began the large-scale emission of these gases keepsthe planet about 33°C warmer than it would be otherwise.13

This natural greenhouse effect, by providing protection fromthe loss of heat, has made most life on Earth possible. Thefunctioning of the carbon cycle has provided a good part ofthis protection; but human activities such as the combustionof fossil fuels, large-scale industrial pollution, deforestationand land-use changes, among others, have led to a build-upof GHGs in the atmosphere together with a reduction of thecapacity of oceans and vegetation to absorb GHGs. Thisattack on the natural carbon cycle on two fronts has reducedthe Earth’s natural ability to restore balance to the carboncycle and is now resulting directly in the current globalchanges in average temperatures.

Looking back to the Earth’s history, it is not surprisingthat its climate system has always changed.14 Yet, a remark-able stability is also evident, with variations in temperaturewithin a narrow range over thousands of years before the


Figure 1.1

Cities in relation tocurrent climate-relatedhazards

Note: The urban areas includedin this figure have populationsgreater than 1 million. Thehazard risk represents acumulative score based on riskof cyclones, flooding, landslidesand drought. A score of ‘0’denotes ‘low risk’ and ‘10’denotes ‘high risk’.

Source: based on de Sherbininet al, 2007, Figure 1

Table 1.2

Urban population indifferent ‘ecozones’, byregion (2000 and 2025)

Share of urban population (%)Ecozone Year Africa Asia Europe North America Oceania South America World

Coastal 2000 62 59 83 85 87 86 652025 73 70 87 89 90 92 74

Low-elevation coastal zone 2000 60 56 80 82 79 82 612025 71 68 85 86 83 90 71

Cultivated 2000 38 42 70 75 67 67 482025 48 55 75 81 72 80 59

Dryland 2000 40 40 66 78 49 61 452025 51 51 70 84 60 75 55

Forested 2000 21 28 53 64 36 53 372025 31 41 59 72 40 68 47

Inland water 2000 51 47 78 84 77 71 552025 62 58 82 88 80 83 64

Mountain 2000 21 27 46 50 11 54 322025 30 40 53 60 13 67 43

Continent average 2000 36 42 69 74 66 66 492025 47 55 75 80 70 78 59

Source: Balk et al, 2009

industrial era.15 Particularly striking about the currentchanges are the speed and intensity at which transforma-tions in the greenhouse effect have been fostered by theexponential growth in concentrations of CO2 and otherGHGs during the industrial era: the increase of about 100parts per million since the dawn of industrialization has ledto a dramatic alteration of both the carbon cycle and theclimate system.16 An analysis of this period reveals thathuman actions are pushing the Earth’s climate beyond atipping point where changes in human behaviour and sys-tems will no longer be able to mitigate the effects of climatechange.

It is undeniable that the Earth’s climate is warming.This is evident from models and observations at global and

continental levels (see Figure 1.3), and from the workleading up to and including the Fourth Assessment Report ofthe Intergovernmental Panel on Climate Change (IPCC),according to which there was an increase of 0.74°C during1906 to 2005. It has been further validated and strength-ened by research published afterwards, according to whichthe observed increase in global mean surface temperaturesince 1990 is 0.33°C.17 Since the onset of the industrial era,concentrations of CO2 and methane (CH4) have increased,with an increase of 70 per cent during the 1970 to 2004period, and urban centres have played a key – though not yetfully understood – role in this process (see Chapter 3). Mostimportant to this discussion, current research validates thatthere have been changes in the frequency and severity of

It is undeniable thatthe Earth’s climateis warming


Box 1.1 Climate change-related terminology

Sources: based on IPCC, 2007b; European Commission, 2007; Nodvin and Vranes, 2010

Adaptation: initiatives and measures to reduce thevulnerability of natural and human systems againstactual or expected climate change effects.

Adaptive capacity: the whole of capabilities, resourcesand institutions of a country or region to implementeffective adaptation measures. Adaptive capacity isthe opposite of vulnerability (see below).

Adaptation deficit: the lack of adaptive capacity to dealwith the problems associated with climate variability.Many cities, and at least some of their populations,already show adaptive deficits within the currentrange of climate variability without regard to anyfuture climate change impacts. In many such citiesand smaller urban centres, the main problem is thelack of provision for infrastructure (all-weatherroads, piped water supplies, sewers, drains, electricity, etc.) and the lack of capacity to addressthis. This is one of the central issues with regard toadaptation because most discussions on this issuefocus on adjustments to infrastructure – but infrastructure that is not there cannot be climate-proofed. Funding for ‘adaptation’ has little value ifthere is no local capacity to design, implement andmaintain the needed adaptation.

Aerosols: airborne solid or liquid particles, with atypical size of between 0.01 and 10 micrometres (1millionth of 1 metre) that reside in the atmospherefor at least several hours. Aerosols may be of eithernatural or anthropogenic origin. Aerosols may influ-ence climate in several ways: directly throughscattering and absorbing radiation, and indirectlythrough acting as cloud condensation nuclei ormodifying the optical properties and lifetime ofclouds.

Anthropogenic: resulting from or produced by humanbeings.

Carbon intensity: the amount of emission of CO2 perunit of gross domestic product (GDP).

Climate change: a change in the state of the climatethat can be identified (e.g. by using statistical tests)by changes in the mean and/or the variability of itsproperties, and that persists for an extended period,typically decades or longer. Climate change may be due to natural processes, or to persistent anthropogenic changes in the composition of theatmosphere or in land use.

Carbon cycle: the flow of carbon (in various forms –e.g. as CO2) through the atmosphere, ocean, terres-trial biosphere and lithosphere.

Carbon footprint: the total amount of emissions ofGHGs caused by a product, an event and an organi-zation. The concept of carbon footprint is a subsetof the ecological footprint.

Carbon sequestration: the process of increasing theuptake of carbon-containing substances, in particularCO2, by reservoirs other than the atmosphere, suchas forests, soils and other ecosystems.

Climate variability: variations in the mean state andother statistics (such as standard deviations, theoccurrence of extremes, etc.) of the climate on allspatial and temporal scales beyond that of individualweather events. Variability may be due to naturalinternal processes within the climate system, or tovariations in natural or anthropogenic externalforcing.

Ecological footprint: a measure of human demand onthe Earth’s ecosystems that compares humandemand with planet Earth’s ecological capacity toregenerate. It represents the amount of biologicallyproductive land and sea area needed to regeneratethe resources that a human population consumesand to absorb and render harmless the corres-ponding waste.

Energy intensity: the ratio of energy use to economicor physical output. At the national level, energy

intensity is the ratio of total primary energy use orfinal energy use to GDP. At the activity level, one canalso use physical quantities in the denominator (e.g. litres of fuel per vehicle kilometre).

Global warming: the documented increase in theaverage temperature of the Earth’s near-surface airand sea surface temperatures based on recordssince the 1880s and the projected continuation ofthese increasing temperatures.

Greenhouse gases (GHGs): those gaseous constituentsof the atmosphere, both natural and anthropogenic,that absorb and emit radiation at specificwavelengths within the spectrum of thermal infraredradiation emitted by the Earth’s surface, the atmos-phere itself and by clouds. This property causes thegreenhouse effect.

Greenhouse effect: the process by which GHGs trapheat within the surface–troposphere system.

Mitigation: technological change and substitution thatreduce resource inputs and emissions per unit ofoutput. Mitigation means implementing policies toreduce GHG emissions and enhance sinks.

Resilience: the ability of a social or ecological systemto absorb disturbances while retaining the samebasic structure and ways of functioning, the capacityfor self-organization, and the capacity to adapt tostress and change.

Vulnerability: the degree to which a system is suscep-tible to, and unable to cope with, adverse effects ofclimate change, including climate variability andextremes. Vulnerability is a function of the character,magnitude and rate of climate change and variationto which a system is exposed, its sensitivity and itsadaptive capacity.

storms, precipitation, droughts and other weather extremesof relevance, all of which have impacts on urban centres (seeBox 1.2).

The types of greenhouse gases18

Various human activities result in the production of GHGs.Water vapour is the most abundant GHG in the atmosphere;but its abundance means that human activities have only asmall influence on its concentration. However, human actionmay generate feedback mechanisms that inadvertently havemuch larger effects on the concentration of this gas. Thefour most important types of GHGs produced by humanactivities are CO2, methane, nitrous oxide (N2O), and thehalocarbons (hydrofluorocarbons and perfluorocarbons) andother fluorinated gases.19 These GHGs are produced fromvarious sources, but can also be removed from the atmos-phere by various processes or activities, referred to as‘sinks’.

These gases do not all have the same impacts uponclimatic change, so are often described using their CO2equivalent value (CO2eq). This is a useful tool for compar-ing emissions, although it does not imply a directequivalence because of the different time-scales over whichthese effects take place. Because of this, the gases may beallocated a global warming potential value that takes intoaccount both the time for which they remain in the atmos-


Box 1.2 Recent changes in climate of relevance to urban areas

Sources: a IPCC, 2007d; b Füssel, 2009; c IPCC, 2007d, p8

Figure 1.2

Schematic diagram ofthe greenhouse effect

Source: adapted fromhttp://web.chjhs.tp.edu.tw/~j-bio/warmhouse/images/v1.gif

SUN

Atmosphere

SpaceSolar radiationfrom the sun

Part of the solar radiation isreflected by the atmosphere

and the Earth’s surfacePart of the infrared radiation

passes through the atmosphereand is lost in space

Most of the infraredradiation is absorbedand re-emitted byGHGs and thisincreases the Earth’stemperature

Solar radiationpasses through theEarth’s atmosphere

Earth’s surface Infrared radiationis emitted from theEarth’s surface

Most of the solar radiationis absorbed by theEarth’s surface and warms it

Rising temperatures• 11 of the last 12 years rank among the 12 hottest years on

record since 1850, when sufficient worldwide temperaturemeasurements began. The eight warmest years have alloccurred since 1998.a

• Over the last 50 years, ‘cold days, cold nights, and frost havebecome less frequent, while hot days, hot nights, and heatwaves have become more frequent’.c

Increasingly severe weather• The intensity of tropical cyclones (hurricanes) in the North

Atlantic has increased over the past 30 years, which corre-lates with increases in tropical sea surface temperatures.a

According to several recent studies, the frequency of strongtropical cyclones has increased during recent decades in allworld regions. Other studies suggest that the intensity ofstrong cyclones will further increase in the future.b

• Storms with heavy precipitation have increased in frequencyover most land areas. Between 1900 and 2005, long-termtrends show significantly increased precipitation in easternparts of North and South America, Northern Europe, andNorthern and Central Asia.a

• Between 1900 and 2005, the African Sahel, theMediterranean, Southern Africa and parts of Southern Asiahave become drier, adding stress to water resources in theseregions.a

• Droughts have become longer and more intense, and haveaffected larger areas since the 1970s, especially in the tropicsand subtropics.a

• More recent climate models point to the fact that the differ-ence between humid and arid regions in terms of extreme

events is projected to become even greater under a changingclimate.b

Rising sea levels• Since 1961, the world’s oceans have been absorbing more

than 80 per cent of the heat added to the climate, causingocean water to expand and contributing to rising sea levels.Between 1993 and 2003, ocean expansion was the largestcontributor to sea-level rise.a More recent figures on sea-level rise are substantially higher than the model-basedestimates in the IPCC’s Fourth Assessment Report, which didnot include ice-sheet dynamics.b

• Melting glaciers and losses from the Greenland and Antarcticice sheets have also contributed to recent sea-level rise (seebelow).a

Melting and thawing• Since 1900, during winters in the Northern Hemisphere,

there has been a 7 per cent loss in the seasonally average areacovered by frozen ground. According to the United NationsEnvironment Programme (UNEP) and the World GlacierMonitoring System,a the average annual melting rate ofmountain glaciers has doubled since 2000, in comparison withthe already accelerated melting rates observed in the twodecades before. Mountain glaciers and snow cover havedeclined worldwide.b

• Although the current and future contribution to sea-level risefrom Antarctica is subject to large uncertainties, recentstudies using extensive satellite observations found that lossof Antarctic sea ice increased by 75 per cent during the tenyears between 1996 and 2006.b

phere and their relative effectiveness in causing the green-house effect. The global warming potential is a measure ofthe contribution that different GHGs make to globalwarming. It takes into account the extent to which thesegases absorb warming radiation and the length of time thatthey remain in the atmosphere. The warming potential ofCO2 is used as the baseline against which this is measured(see also Table 1.3).

n Carbon dioxide Carbon dioxide (CO2) is the most important anthropogenicGHG. Indeed, CO2 emissions are often used synonymouslywith contributions to climate change. The main sources ofatmospheric CO2 are from the burning of fossil fuels, whichis responsible for more than 75 per cent of the increase inatmospheric CO2 since pre-industrial times. This energy

from fossil fuels is used in transportation, heating andcooling of buildings, and manufacture of cement and othergoods – all of which are substantial activities in urban areas.Land-use changes – deforestation and changing agriculturalpractices – account for the remaining 25 per cent of CO2emissions. Deforestation also reduces an important sink forthe gas, as plants absorb CO2 in the process of photosynthe-sis. The average annual CO2 emissions from fossil fuels,cement production and gas flaring were 12.5 per centgreater during the period of 2000 to 2005 than during 1990to 2000. The global atmospheric concentration of CO2 in2005 was approximately 379 parts per million – an increasefrom a pre-industrial value of about 280 parts per million.The approximate lifetime of CO2 in the atmosphere is 50 to200 years.


Carbon dioxide(CO2) is the mostimportant anthropogenic GHG

The main sources ofatmospheric CO2 arefrom the burning offossil fuels … usedin transportation,heating and coolingof buildings, andmanufacture ofcement and othergoods

Figure 1.3

Global and continentaltemperature change

Note: The black line in thefigures represents observedsurface temperature changes.The light grey band representshow the climate would haveevolved over the past centuryin response to natural factorsonly. The dark grey bandrepresents how the climatewould have changed inresponse to both human andnatural factors. The overlap ofthe dark grey band and blackline suggests that humanactivity very likely causedmost of the observed increasesince the mid 20th century.Lines are dashed where spatialcoverage is less than 50 percent.

Source: IPCC, 2007d, p11

Table 1.3

Major characteristics ofthe most importantGHGs

Carbon dioxide Methane Nitrous oxide Halocarbonsa

(CO2) (CH4) (N2O) CFC- 11 CFC- 12 HFC- 23

Atmospheric concentration: parts per million (ppm)/billion (ppb)/trillion (ppt):Pre-industrial times 280 ppm 715 ppb 270 ppb – – –1998 366 ppm 1763 ppb 314 ppb 264 ppt 534 ppt 14 ppt2005 379 ppm 1774 ppb 319 ppb 251 ppt 538 ppt 18 pptChange in atmospheric concentration (%):Pre-industrial times–2005 +31 +147 +16 ∞ ∞ ∞ 1998–2005 +4 +1 +2 –5 +1 +29 Approximate lifetime in the atmosphere (years) 50–200 12 114 45 100 270 Global warming potential relative to CO2 in 100 years 1 25 298 4750 10,900 14,800 Radiative forcing 2005 (watts per square metre) 1.66 0.48 0.160 0.063 0.170 0.0033 Change in radiative forcing 1998–2005 (%) +13 – +11 –5 +1 –

Notes: a For details on other halocarbons, see IPCC (2007d). ∞ = infinity.

Sources: Forster et al, 2007; IPCC, 2007d

n MethaneMethane is emitted into the atmosphere through a variety ofhuman activities, including energy production from coal andnatural gas, waste disposal in landfills, raising ruminantanimals (e.g. cattle and sheep), rice cultivation and theburning of biomass. Wetlands are the main natural source ofmethane, although it is also emitted from the oceans and bythe activities of termites. In 2005, methane accounted forabout 1774 parts per billion of the atmosphere, more thantwice its pre-industrial value – and these current levels aredue to the continued human-induced emissions of the gas.Despite this apparently low concentration, methane is a

powerful GHG that has a significant impact upon climatechange. It is relatively short lived in the atmosphere with anapproximate lifetime of 12 years. Over a 100-year period, ithas 25 times the global warming potential of CO2; but in theshort term this is much stronger: it has a global warmingpotential 72 times that of CO2 over a 20-year time horizon.

n Nitrous oxideNitrous oxide is emitted from fertilizers and the burning offossil fuels, and is also released by natural processes in soilsand oceans. About 40 per cent of total nitrous oxideemissions result from human activities. In 2005, atmos-


Figure 1.4

Fluorinated gases1.1%

CO2 fossil fuel use56.6%

CO2 (other)2.8%

CO2 (deforestation,decay of biomass, etc)

17.3%

Methane14.3%

Nitrous oxide7.9%

Transport13.1%

Residential andcommercial buildings

7.9%

Industry19.4%

Agriculture13.5%

Forestry17.4%

Waste and wastewater2.8%

Energy supply25.9%

1970 1980 1990 2000 2004

Billi

on t

onne

s of

CO

2eq

per

year

60

50

40

30

20

10

0

28.7

35.639.4

44.7

49.0

CO2 from fossil fuel use and other sources

Methane from agriculture, waste and energy

CO2 from deforestation, decay and peat

Nitrous oxide from agriculture and others

Fluorinated gases

a) b)

c)

Global anthropogenicGHG emissions

Notes: (a) Global annualemissions of anthropogenicGHGs from 1970 to 2004; (b) share of different anthropogenic GHGs in totalemissions in 2004 in terms ofCO2 equivalents (CO2eq); (c)share of different sectors intotal anthropogenic GHGemissions in 2004 in terms ofCO2eq (forestry includesdeforestation).

Source: IPCC, 2007a

Table 1.4

Total and per capitaGHG emissions (‘top20 countries’)

GHG emissions (2005)a CO2 emissions (2007)b

Country Thousand Percentage of Metric tonnes Thousand Percentage Metric tonnes of Percentage metric tonnes total CO2eq of CO2eq metric tonnes of total CO2 per capita change in CO2

of CO2eq per capita of CO2 CO2 (2005–2007)

China 7,303,630 18.89 5.60 6,538,367 22.30 4.96 16.5US 7,211,977 18.66 24.40 5,838,381 19.91 19.38 –0.1India 2,445,328 6.33 2.23 1,612,362 5.50 1.43 14.3Russian Federation 2,115,042 5.47 14.78 1,537,357 5.24 10.82 1.4Japan 1,446,883 3.74 11.32 1,254,543 4.28 9.82 1.0Brazil 1,079,576 2.79 5.80 368,317 1.26 1.94 5.2Germany 972,615 2.52 11.79 787,936 2.69 9.58 –2.7Canada 725,606 1.88 22.46 557,340 1.90 16.90 –0.5UK 672,148 1.74 11.16 539,617 1.84 8.85 –0.8Mexico 627,825 1.62 6.09 471,459 1.61 4.48 6.9Indonesia 625,677 1.62 2.85 397,143 1.35 1.77 16.4Australia 601,444 1.56 29.49 374,045 1.28 17.75 2.7Iran 598,479 1.55 8.66 495,987 1.69 6.98 16.2Italy 571,378 1.48 9.75 456,428 1.56 7.69 –2.5France 542,980 1.40 8.92 371,757 1.27 6.00 –5.2Republic of Korea 535,836 1.39 11.13 503,321 1.72 10.39 8.7South Africa 499,842 1.29 10.66 433,527 1.48 9.06 6.2Spain 457,776 1.18 10.55 359,260 1.23 8.01 1.6Saudi Arabia 439,516 1.14 19.01 402,450 1.37 16.66 9.6Ukraine 427,297 1.11 9.07 317,537 1.08 6.83 –2.8Other developed countries 2,237,764 5.79 9.46 1,791,983 6.11 7.55 1.1Rest of Asia and Pacific 3,527,583 9.13 3.51 2,460,617 8.39 2.37 7.3Rest of Latin America and the Caribbean 1,329,867 3.44 5.04 749,694 2.56 2.77 10.0Rest of Africa 1,659,120 4.29 1.90 699,867 2.39 0.77 4.1World total 38,655,189 100.00 6.00 29,319,295 100.00 4.45 6.0

Note: The world totals include only emissions that have been accounted for in national inventories.

Source: a http://data.worldbank.org/indicator, last accessed 21 October 2010; b http://mdgs.un.org/unsd/mdg, last accessed 21 October 2010; see also Statistical Annex, Tables B.7 and B.8

pheric nitrous oxide levels were 18 per cent higher than pre-industrial levels, at 319 parts per billion. The gas has alifetime in the atmosphere of 114 years, and over a 100-yearperiod has a global warming potential that is 298 timesgreater than CO2.

n HalocarbonsHalocarbons – including chlorofluorocarbons (CFCs) andhydrochlorofluorocarbons (HCFCs) – are GHGs that areproduced solely by human activities. CFCs were widely usedas refrigerants before it was discovered that their presencein the atmosphere caused the depletion of the ozone layer.International regulations to protect the ozone layer – notablythe Montreal Protocol of 1987 – have been successful inreducing their abundance and their contribution to globalwarming. However, the concentrations of other industrialfluorinated gases (hydrofluorocarbons, perfluorocarbons andsulphur hexafluoride) are relatively small but are increasingrapidly. Although these gases occur in much smaller concen-trations than CO2, methane and nitrous oxide, some of themhave extremely long lifetimes and high global warmingpotentials, which means that they are important contributorsto global warming. For example, HFC-23 (CHF3) has alifetime of 270 years and a global warming potential over100 years 14,800 times greater than CO2.

The causes of climate change

The main human sources of GHGs contributing to globalwarming are the dramatic rise in energy use, land-usechanges and emissions from industrial activities (see Figure1.4). Furthermore, between 1970 and 2004, changes infactors such as increased per capita income (up 77 per cent)and population growth (up 69 per cent) have favouredincreases in GHG emissions. These have been, to a limitedextent, offset by increases in efficiency and/or reductions inthe carbon intensity of production and consumption; but theoverall global trend has still been towards large increases inanthropogenic GHG emissions.

Not every country has contributed at the same levelto global warming. In 2007, developed countries accountedfor 18 per cent of the world’s population and 47 per cent ofglobal CO2 emissions, while developing countries accountedfor 82 per cent of the population and 53 per cent of CO2emissions.20 Developing countries, therefore, generated only25 per cent of the per capita emissions of developed coun-tries. A select number of developed countries and majoremerging economy nations are the main contributors to totalCO2 emissions (see Table 1.4). In fact, three developedcountries (Australia, the US and Canada) have among thehighest CO2 emissions per capita, while some developingcountries lead in the growth rate of CO2 emissions (e.g.China and Brazil). These uneven contributions to the climatechange problem are at the core of both internationalenvironmental justice issues and the challenges that theglobal community faces in finding effective and equitablesolutions (see Chapter 2).

In this context, humanity is facing two mainchallenges that urban centres can to help address:

1 There is a need to adapt, at least to some amount ofcontinued warming, because even if the concentrationsof GHGs and aerosols are kept constant at year 2000levels, ‘a further warming of about 0.1°C per decadewould be expected’.21

2 There will also be a need to mitigate – that is, to achievedevelopment paths that bring about a peaking ofemissions by 2015 and a stabilization of GHG concen-trations in the atmosphere at about 445 to 490 partsper million by volume of CO2 equivalents (CO2eq) bythe end of the century.22 This path would keep globalaverage temperature increases within 2°C to 2.4°Cabove pre-industrial levels, in keeping with the objectiveoutlined in the United Nations Framework Conventionon Climate Change, Article 2 (see Chapter 2).


Urbanization level

4.54.03.53.02.5

Nat

ural

log

CO

2 per

cap

ita

–4

–5

–6

–7

–8

–9

–10

Natural log GDP per capita

98765

Nat

ural

log

CO

2 em

issi

ons

per

unit

GD

P

–12

–13

–14

–15

–16

10

Figure 1.5

Relationships betweenurbanization levels andCO2 emissions percapita

Source: Romero Lankao et al,2008

Figure 1.6

Carbon intensity andeconomicdevelopment (2003)

Source: Romero Lankao et al,2008

Regarding the amount of GHG emissions that urban areascontribute to the atmosphere, it has been claimed (correctlyor incorrectly) that although cities take up only 2 per cent ofthe Earth’s land mass, they are responsible for as much as 75per cent of the GHGs that are released into the atmos-phere.23 Indeed, many of the sources of these emissions areurban. The myriad of urban processes accounting for theseemissions are combustion of fossil fuels by commercial andresidential buildings or electricity generating plants forheating and air conditioning, the commercial and individualuse of energy for running motor vehicles for transportation,and energy used in industrial processes. Urban householdsmay also consume fuels more directly, in heaters andcookers, or indirectly in air conditioning or electric heating.Land-use changes induced by urban growth may lead todeforestation and reductions in the uptake of CO2 by vegeta-tion. Landfill sites taking up urban wastes also generatemethane. Cement, as a construction material of primaryimportance to the development of urban infrastructure, aswell as of commercial and residential buildings, also has alarge carbon footprint due to an energy-intensive manufac-turing process and high energy cost for transporting thisdense material. Lastly, many activities, such as agriculture,livestock production, mining, timber collection and lumberproduction, increase GHG emissions as direct emitters orreduce the uptake of these gases by vegetation. While theseare often undertaken outside the boundaries of urbancentres, they are aimed at satisfying urban needs for food,raw materials, forest products and construction materials.

As will be shown in Chapter 3, it remains unclear justhow accurate existing figures on GHG emissions by citiesare. Many different criteria have been used to measure theseemissions, and the choice by researchers to use one or theother can greatly skew the final calculations on how largethose contributions are.24 For instance, if GHG emissions areallocated based on the generating activities within urbancentres (the production-based approach), then these centresemit between 30 and 40 per cent of all anthropogenicGHGs. The proportion of GHGs that should be attributed tocities would be higher, however, if emissions were assignedto the consumers (i.e. to the home or business or organiza-tional location of those whose demand for goods, services orwaste disposal or travel creates the need for those goods orservices that produce the GHG emissions). Under thisconsumption-based approach, cities’ contribution to globalGHG emissions would rise to almost half of all globalemissions.

A dynamic, complex and strong link exists betweeneconomic development, urbanization and CO2 emissions(see Figures 1.5 and 1.6). Urban contributions to CO2emissions seem to be based at least in part on the size of thenational economy in which the urban centres are located (asmeasured by total GDP in constant US dollars) and the struc-ture of that economy (i.e. whether it is predominantly indus-trial or service oriented). Although the relations betweentotal emissions and the size of a country’s economy havebeen weakening since the 1960s, there is still a strong corre-lation, with total emissions rising with the size of theeconomy (see Figure 1.6). Total energy used per unit of GDP

went down by 33 per cent between 1970 and 2004, yet therate of improvement has not been enough to globally reduceGHG emissions, which are rising beyond the worst-casescenario and have already resulted in an Earth that is 0.8°Cwarmer on average than it was in pre-industrial times. Basedon the significant roles that they play in their countries’economies, urban areas can be seen as playing a major role inthis connection.25

Nevertheless, the relationship between levels ofurban development, as measured by GDP and levels ofGHG emissions, is not so straightforward. It is clear thatdifferences in GHG emissions result from the peculiaritiesand weight of different sectors, as shown in the nextsection.

FRAMEWORK FOREXPLORING THE LINKAGESBETWEEN URBAN AREASAND CLIMATE CHANGEReducing the contribution of cities to climate change, ormitigation, requires an adequate understanding of thedrivers of urban GHG emissions, while effective adaptationmust be based on a good understanding of what makes citiesand their constituent socio-economic groups either vulnera-ble or resilient to climate change impacts. This sectiontherefore focuses on the drivers of GHG emissions in urbanareas and the concepts of vulnerability and resilience asframeworks for both analysis and for formulating mitigationand adaptation policy options.

Drivers of urban contributions to GHG emissions

Since the industrial revolution, urban centres have concen-trated industries, construction, transportation, householdsand other activities that release large quantities of GHGs.Other sources that occur both inside and outside cities, butserve urban development, include deforestation and otherland-cover changes, agriculture, waste disposal, powergeneration, and refrigeration and air conditioning. Chapter3 presents findings from a wide range of urban emissionsinventories to show how the data on urban emissions variesfrom place to place, and how the figures on emissions varydepending on the approaches used (i.e. consumption- orproduction-based approaches). It is therefore important tohave a framework for understanding the levels and driversof emissions by different demographic and economicsectors, buildings and infrastructures within, or serving,urban areas.

The exploration of how urban centres contribute toclimate change requires an understanding of how transporta-tion, heating and cooling systems, industries and other urbanactivities and infrastructures act both as emitters and directcauses of climate change. They create two main categories ofimpacts on the carbon cycle and the climate system:


It remains unclearjust how accurateexisting figures onGHG emissions bycities are

Since the industrialrevolution, urbancentres haveconcentrated industries, construction, transportation,households andother activities thatrelease large quantities of GHGs

The exploration ofhow urban centrescontribute toclimate changerequires an under-standing of how …urban activities andinfrastructures actboth as emitters anddirect causes ofclimate change

1 Changes related to the emission of aerosols, GHGs andsolid wastes. GHGs are the main source of changes inthe climate system. Not only do they change the dynam-ics of the carbon cycle, but together with aerosols theyalso generate changes in the Earth’s radiation thatinduce climate change.26 Wastes affect the growth,function and health of vegetation and of ecosystems ingeneral.27

2 Land-use related changes. Urbanization is a process thatchanges the uses of land and by creating impervioussurfaces, filling wetlands and fragmentation of ecosys-tems has disproportional impacts upon the carbon cycle.The built environment of urban areas is also a forcingfunction on the weather–climate system of urbancentres because it is a source of heat and a poor storagesystem for water.

Both within and across cities, different populations,economic activities and infrastructures contribute at differ-ent levels to global warming. Some studies point to the factthat gender inequities exist both in energy use and GHGemissions and that the differences are related not only towealth, but to behaviour and attitudes. For instance, womentend to buy efficient electric appliances, while men tend toundertake efforts to insulate their houses. Men tend to eatmore meat, while women tend to eat more vegetables, fruitsand dairy products. Men tend to use more private motorizedtransport than women, and to use larger, more fuel-consum-ing vehicles.28

Urban centres in developing countries have lowerlevels of emissions per capita than cities in developedcountries.29 Houston and Washington, DC (US), for instance,have carbon emissions that are about 9 to 18 times higherthan those in São Paulo (Brazil), Delhi and Kolkata (India)(see Chapter 3). Yet, other wealthy cities such as Stockholm(Sweden) and Barcelona (Spain) have lower levels ofemissions per capita than some South African cities. This isbecause several interrelated factors shape or determine thepatterns of energy use and emissions by different popula-tions and sectors.

The climate and natural endowments of an urban areaare significant factors shaping its energy-use pattern. A citylocated in high latitudes, for instance, might consume moreenergy to heat its buildings and houses than one situated inthe tropics; and conversely, an urban centre located in thetropics might consume more energy for air conditioning.Thus, climate change will affect energy consumption behav-iour in many urban areas of the world.

Weather undoubtedly plays a role in cities’ carbonfootprints, but does not act alone. For instance, manyrelatively colder urban areas in the northeast of the US havelarger residential carbon footprints because they rely oncarbon-intensive home heating fuels such as fuel oil. Warmareas in the south, likewise, have large residential carbonfootprints because they rely on carbon-intensive air condi-tioning.30 The carbon intensity of the fuels used is, hence,another key factor. For instance, the carbon intensity of coalis almost two times higher than the carbon intensity ofnatural gas.

The economic base of a city is another importantfactor. In Beijing and Shanghai (China), industry contributes43 and 64 per cent of the total emissions, respectively.31

Industrial emissions of GHGs in cities elsewhere are muchlower: 28.6 per cent in Mexico City, 7 per cent in London(UK), 9.7 per cent in São Paulo (Brazil), and 10 per cent inTokyo (Japan) and New York (US). This reveals that manycities have already transitioned to service-based urbaneconomies and, thus, have been able to reduce their carbonfootprints. The differences reflect a shifting internationalpattern in the location of industrial activities – a patterndetermined by differences in profitability, costs and environ-mental legislation among cities.32 The current patternreflects the fact that China has become the main manufac-turer of commodities for the world, allowing developedcountries to shift responsibility for their own GHG emissionsin spite of the fact that their consumer-driven impact uponthe market has created much of the need for a high indus-trial output in China. This international shifting of thelocation of industrial production calls for the use ofconsumption-based approaches, and not only production-based ones, in the measurement of emissions in order tohave a true picture of responsibility for industrial emissionsamong and within countries and urban areas.33

Affluence has been repeatedly acknowledged as asignificant driver of GHG emissions and other environmentalimpacts; but again it does not act alone – rather, togetherwith such factors as technology, natural endowments andequity. According to ecological modernization theory,environmental problems such as climate change areaddressed by development or modernization. A structuralchange, or shift, to less carbon-intensive societies occurs atthe macroeconomic level through the development of newand less carbon-intensive technologies whose use is inducedby market mechanisms.34

As an economy develops (modernizes), sectors suchas agriculture and fisheries are replaced by manufacturingindustries and, with further development, service industries.Ecological modernization theorists argue that economicgrowth within developing economies will follow a naturalpath, driven by economic forces and market dynamics, fromhigher to lower states of environmental stress. The environ-mental impacts of economic growth, thus, increase in theearly stages of development, but stabilize and then declineas economies mature. The process is depicted by an invertedU-shape curve, also known as the Environmental KuznetsCurve. Indeed, the relation between national carbon inten-sity and level of economic development has changed fromessentially linear in 1965 to essentially curvilinear in1990.35 The tendency to an essentially curvilinear relationwas still valid for the year 2003 (see Figure 1.6). A linearrelation means that a one unit increase in GDP essentiallytranslates to a similar increase in emissions, while in a curvi-linear relation a one unit increase relates to a smaller thanone unit increase in emissions. However, at least part of thistendency might be understood in terms of the shifting ofmanufacturing activity to other areas due to economic, polit-ical and environmental factors, as illustrated in the exampleof China given above. Because developed countries’


Gender inequitiesexist both in energyuse and GHGemissions

Urban centres indeveloping countrieshave lower levels ofemissions per capitathan cities in developed countries

The internationalshifting of thelocation of industrialproduction calls forthe use of consumption-basedapproaches … in themeasurement ofemissions … amongand within countriesand urban areas

economies have become service based and because theirindustrial production has been relocated to some developingcountries, GHGs emitted by their urban areas havedecreased. However, their responsibility for that percentageof the GHGs emitted in the industrial manufacturingcountries producing goods for them should be accounted tothem as the consumers creating the need for the goods andnot to the manufacturing country.36 Some researchers havesuggested that this change in the attribution of GHGs wouldalter the features of the curve.37

Affluence theory has empirical and political relevancefor this Global Report for two reasons. While the ‘environ-mental burdens of urban poverty primarily affect the poorliving in the immediate locality’, the environmental burdensof affluence, such as climate change, can affect both rich andpoor people around the globe; but these also tend to falldisproportionately upon the poor.38 The second reason,relevant to the debate around climate change impacts uponcities, follows from the fact that the very urban dwellersmost at risk from local environmental degradation – the poor– seem also to be most at risk from floods, heat waves,storms and other climate-related threats.39

It can be misleading to concentrate on urbanemissions per capita, as there are very large differentialswithin urban centres. Both gender and socio-economicequity is, therefore, a key dimension affecting GHG emis-sions by urban populations and activities. There is noadequate information to provide an accurate picture on therole of equity in determining different levels of emissionsamong demographic sectors of an urban area. Yet, someexamples can be used to draw preliminary conclusions.According to a study on the per capita emissions footprintsof single-person households in Germany, Norway, Greeceand Sweden, on average men consumed between 6 per cent(Norway) and 39 per cent (Greece) more energy thanwomen, and this gender difference is independent of incomeand age.40 The per capita emissions of Dharavi, a predomi-nantly low-income, high-density inner-city neighbourhood of

Mumbai (India), are a tiny fraction of the per capitaemissions of high-income districts of Mumbai, where a highproportion of the population commutes to work by car.41

According to human ecologists, the size, growth,structure and density of population are key determinants ofcities’ GHG emissions and other environmental impacts.42 Anegative correlation exists between population density andatmospheric GHG emissions; for instance, a 1 per centincrease in the density of urban areas would relate to approx-imately 0.7 per cent decline in carbon monoxide (CO)pollution at the city level, with other factors held constant.43

Spatially compact and mixed-use urban developments havesignificant benefits in terms of GHG emissions.44 However,attention also needs to be given to other explaining factors,such as land-use patterns and the layout of the transporta-tion system.45 Furthermore, urban density poses a dilemma:while ‘tailpipe emissions and fossil-fuel consumption aregreatly increased with urban sprawl’, levels of humanexposure to emissions of other pollutants (e.g. nitrogendioxide) might actually increase with density if no measuresare undertaken to reduce atmospheric emissions.46 Theimplications of urban form on climate change mitigation andadaptation are discussed in Chapters 5 and 6.

Urban vulnerability and ‘resilience’

As described above, urban settlements are already at riskfrom sea-level rise, droughts, heat waves, floods and otherhazards that climate change is expected to aggravate. Yet, afocus on the exposure to these hazards alone is insufficientto understand climate change impacts upon urban centres,their populations and economic sectors. Attention to urbanresilience, development, socio-economic and gender equity,and governance structures as key determinants of adaptivecapacity and actual adaptation actions is also necessary.Many scholars and practitioners view resilience in thecontext of responses to hazards and recovery fromdisasters.47 In this view:

• Cities can increase or reduce the impacts of such hazardsas floods and heat waves as a result of their socio-environ-mental history. Urban activities invariably alter theirenvironment, but two results are possible: environmentaldegradation and reduced resilience (see Box 1.3), orurban populations’ growing ability to repair damage,sustain the environment and increase cities’ resilience.48

• Urban populations and the different tiers of governmentresponsible for their well-being are resilient if they areable to build capacity for learning and adaptation, andeven capitalize on the learning opportunities that mightbe opened by a disaster. The urban populations ofDhaka and other human settlements of Bangladesh offeran example of this (see Box 1.4).

The significance of urban vulnerability and adaptive capacityto climate impacts can be analysed on at least two distinctlevels: from the perspective of the city as a whole and theway in which it develops; and from the perspective of thecity as it can be broken down to reveal its different socio-


The environmentalburdens ofaffluence, such asclimate change, canaffect both rich andpoor people aroundthe globe; but …tend to fall disproportionatelyupon the poor

The size, growth,structure anddensity of population are keydeterminants ofcities’ GHGemissions

Box 1.3 Mexico City: Environmental degradation and vulnerability

The water management system of Mexico City has developed features which do not allow it tocope with floods and droughts. It is overexploiting not only its water resources by between19.1 and 22.2 cubic metres per second, but also the water of two providing basins (Lerma andCutzamala). According to projections where no consideration is given to global warming,between 2005 and 2030 the population of Mexico City will increase by 17.5 per cent, whilebetween 2007 and 2030 available water will diminish by 11.2 per cent. The situation might getworse if, as expected, climate change brings lower precipitation to this area. Those water userswho already face recurrent shortages during the dry season, or when droughts hit Mexico City,will be especially affected. For example, 81.2 per cent of people affected by droughts during1980 to 2006 live in Netzahualcoyotl, one of the poorer municipalities of the city.

This overexploitation of water resources creates two sources of vulnerability: first,problems of water availability (scarcity) that make water users (especially poor sectors alreadyfacing scarcity) vulnerable to the changes in the availability of water that are expected fromclimate change. Second, groundwater levels are continuously falling, which historically hascaused subsidence (and continues to do so in some areas), thus undermining the foundations ofbuildings and urban infrastructure and increasing the vulnerability of these areas and thepopulations within them to such hazards as heavy earthquakes and rains.

Source: Romero Lankao, 2010

demographic groups’ access to the determinants of adaptivecapacity.

n Urban development can bring increasedvulnerability to climate hazards

The concentration, in urban centres, of people and theirhomes, infrastructure, industries and waste within arelatively small area can have two implications for the urbanimpacts of climate change and other stresses. On the onehand, urban areas can be dangerous places in which to liveand work; their populations can be very vulnerable toextreme weather events or other hazards, with the potentialto become disasters. For instance, the urban concentrationof these elements can generate risk when residential andindustrial areas lack space for evacuation and emergencyvehicle access (as in the case of slums), when high-incomepopulations are lured by low-lying coastal zones or greenareas (as in California or Florida in the US, or Melbourne,Australia), or when lower-income groups, lacking the meansto access safer land, settle on sites at risk from floods orlandslides (as in Rio de Janeiro in Brazil, Mumbai in India andmany urban centres in developing countries).

Urban settlements can increase the risk of ‘concaten-ated hazards’.49 This means that a primary hazard (heavystorm) leads to secondary hazard (e.g. floods creatingcontamination of water supplies, or landslides destroyinghouses and infrastructures). Industrialization, inadequateplanning and poor design are key determinants of secondaryor technological risks. As illustrated by Bogotá (Colombia),Buenos Aires (Argentina) and Santiago (Chile), the popula-tions of many cities are already at risk from exposure to highlevels of pollution, exceeding World Health Organization(WHO) standards in particulate matter and nitrogen dioxideconcentration in the air.50 It is possible that the impacts ofclimate hazards such as heat waves will overlap with pollu-tion events and the urban heat-island effect, and compoundone another, making urban disaster risk management evenmore complex.

On the other hand, the same concentration of people,infrastructure and economic activities in urban centres alsomeans economies of scale for many of the measures thatreduce risks from extreme weather events. These economiesof scale might manifest themselves in a reduced per capitacost of better watershed management, warning systems andother measures to prevent and lessen the risks when a disas-ter threatens or occurs. Furthermore, when provided withpolicies focused on enhancing sustainability and movingfrom disaster response to disaster preparedness, urbansettlements can increase their effectiveness at coping withclimate hazards.

Exposure to current climate hazards is, for manycities, a result of historical location factors and a long devel-opment process. Many cities have developed without consid-eration of the risks that climate change will induce. Mostlarge cities have been built on sites that were originallychosen for trade or military advantage (e.g. Shanghai, China;New York, US; Cartagena, Colombia; and Cape Town, SouthAfrica). In the majority of cases, this has meant that theywere located on the coasts or near the mouths of major

rivers where trade by sea with other coastal cities or byrivers with the interior hinterlands could best be accom-plished. These urban centres then became the hubs of tradefor their countries and, as such, greatly increased theirwealth.

As this wealth continued to build, further develop-ment was fuelled and these areas became engines ofeconomic growth for their countries, attracting more capitalfrom private-sector investment and labour migration fromrural areas and immigration from other countries. Themovement to urban centres continues today and these areashave become magnets of industry and labour without regardto the many environmental risks that are endemic to theseareas and the mounting hazards resulting from climatechange.

n Why are some sectors of the populationmore vulnerable?

Not all demographic segments of the urban population areequally affected by the hazards aggravated by climatechange. The capacity of different urban populations to copeor adapt is influenced not only by age and gender, but also byone or a combination of some or many factors51 (see Chapter4). These factors include:

• Labour, education, health and the nutrition of theindividuals (human capital). As a critical asset, labour islinked to investments in human capital. Health statusdetermines people’s capacity to work; education andskills determine the returns from their labour.

• The financial resources available to people (savings,supplies of credit – i.e. financial capital).

• The extent and quality of infrastructure, equipment andservices (physical capital), some of which are owned byindividuals (e.g. housing).

• Stocks of such environmentally provided assets as soil,land and atmosphere (natural capital). In urban areas,land for shelter is a critical productive asset.

• The quality and inclusiveness of governance structuresand community organizations that provide or managesafety nets and other short- and longer-term responses,or social capital – an intangible asset defined as therules, norms, obligations and reciprocity embedded insocial relations and institutional arrangements.

Urban centres alsomeans economies ofscale for many of themeasures thatreduce risks fromextreme weatherevents

When provided withpolicies focused onenhancing sustainability andmoving from disaster response to disaster preparedness, urban settlementscan increase their effectiveness atcoping with climatehazards


Box 1.4 Capacity to learn and adapt in Bangladesh

Bangladesh is situated in an area at risk from tropical storms, whose intensity and frequencyhave increased over the last years. A hurricane hit Bangladesh in 1991 killing at least 138,000people and leaving as many as 10 million people homeless. Serious efforts have beenundertaken, promoted by local and national governments and international organizations, todecrease the risk from tropical cyclones in the area. These efforts have included the develop-ment of an early warning system and the construction of public shelters to host evacuatedpeople. These improvements were tested in 2007, when between 8 and 10 million Bangladeshiswere exposed to Sidr, perhaps the strongest cyclone to hit the country since 1991.There was a32-fold reduction in the death toll (i.e. 4234 people compared to 138,000) and Bangladesh’scapacity for learning and adaptation was proven (see also Boxes 4.4 and 6.2).

Source: Paul, 2009

Wealthy individuals and households have many of therequirements for higher adaptive capacity. They have moreresources to reduce risks – that is, safer housing, more stablejobs, safer locations to live in, and better means of protectingtheir wealth (e.g. insurance of assets that are at risk).Wealthier groups often have more influence on publicexpenditures. In many urban areas, middle- and upper-income groups have been the main beneficiaries ofgovernment investment in such determinants of adaptivecapacity as infrastructure and services. If government doesnot provide these, higher-income groups have the means todevelop their own provisions for water, sanitation andelectricity, or to move to private developments whichprovide them. Wealthier groups, therefore, have higheradaptive capacity.

Although systematic evidence of the gender implica-tions of climate change at the city level both among wealthyand poor sectors and countries is still lacking,52 someevidence points to the fact that gender gaps exist in access tosuch assets and options as credit, services, education, infor-mation, decision-making power and technology. Forinstance, in sub-Saharan Africa, 84 per cent of women’s non-agricultural employment is informal (compared to 63 percent of men’s).53 The informal sector is also important incapital and large cities, where more than half of all womenare employed in the informal sector (except in South Africaand Namibia), although informal employment is actuallyhigher in small cities and towns and rural areas.54 Due to thissituation, women do not have adequate livelihood optionsand can be particularly vulnerable to disasters. As illustratedby Hurricane Mitch in Honduras and floods in Dhaka,Bangladesh, disaster warnings often do not reach women orare not understood by women. Furthermore, in manyinstances, women cannot evacuate without the authoriza-tion of their husbands.55

Scattered evidence points to the fact that children aremore at risk of being affected by the adverse impacts ofclimate change.56 There are several reasons for this: they arein a stage of rapid development which can be severely inter-rupted by the stress of severe weather events and climatehazards. They are relatively more vulnerable to warm spellsand heat waves, heavy precipitation, droughts and otherclimate hazards because of their immature organs andnervous systems, limited experience and behavioural charac-teristics. This can be intensified by poverty and the difficultchoices that poor households make as they cope withchallenging situations. However, it is also true that ‘withadequate support and protection, children can be extraordi-narily resilient’ when faced with hazards and stresses.57

Very elderly men and women can also be at risk, asillustrated by the high elderly mortality rates in the heatwaves that hit Chicago (US) in 1995 and Europe in 2003.Indeed, as illustrated by research in the cities of London andNorwich (UK), the elderly might feel, falsely, that heat wavesdo not pose a significant risk to them personally.58 Theelderly can also be limited in their capacity to move rapidlyaway from rising floodwaters by their isolation, their healthconditions or their perceptions.

The urban poor tend to be highly vulnerable,especially in developing countries, and may also fall into

other disadvantaged categories that increase vulnerability byalso being women, very young or very old. Many poorpopulations face additional risks: they live in informal settle-ments, live on floodplains, unstable slopes, over river basinsand in other highly risk-prone areas, or work within theinformal economy. They are also constantly faced with thepossibility that governments may forcibly move them off landsites deemed to be vulnerable to weather risks, or they maybe moved simply because other actors want the land theyoccupy for more ‘profitable’ uses, but with the consequencethat they are also moved away from their means of liveli-hood.59

Furthermore, poorer groups are most affected by thecombination of greater exposure to a range of other possibleurban hazards (e.g. poor sanitary conditions and lack ofhazard-removing infrastructure such as drainage). They haveless state provision to help them cope, along with less legal and insurance protection. Low-income groups alsohave far fewer possibilities to move to less dangerous sites.This should not, however, lead to the conclusion that thepoor are merely passive recipients of the risks of climatechange and other hazards. As illustrated by Cavity City inthe Philippines, or the Baan Mankong (‘secure tenure’)programme in Thailand,60 many poor groups have developedmechanisms to adapt. It just means that the structuralissues referred to here pose severe limits to their copingmechanisms and create constraints upon their adaptationoptions.

CONCLUDING REMARKSAND STRUCTURE OF THEGLOBAL REPORTUrbanization and climate change are sources of both devel-opmental and environmental challenges and opportunities.Industrialization and urbanization have been critical compo-nents of rapid economic growth and of technologicalchanges that have contributed to improvements in theeconomy and the quality of life of many urban populationsaround the world. Both have also helped to decrease thecarbon intensity and increase the efficiency of productionand consumption. Yet, notwithstanding these socio-economic and technological achievements, poverty – whichhas increasingly been acquiring an urban face – remains aformidable challenge. ‘The needs remain enormous, withthe number of hungry people having passed the billionmark.’61 Poverty alleviation thus remains the overarchingpriority, especially in developing countries.

Climate change, which is both a developmental andenvironmental issue, complicates the picture in severalways. The impacts of global GHG emissions are currentlymanifest in stronger and more frequent floods, droughts andheat waves, adversely affecting the industries, populationsand governments of many urban centres. Therefore, urbanpopulations and economic sectors are faced with twochallenges: the need to adapt, at least to some amount ofwarming, and the urgency to mitigate the causes of globalclimate change.

Higher-incomegroups … havehigher adaptivecapacity

Women … can beparticularly vulnerable to disasters

Children are more atrisk of beingaffected by theadverse impacts ofclimate change

Poorer groups aremost affected by thecombination ofgreater exposure toa range of otherpossible urbanhazards (e.g. poorsanitary conditionsand lack of hazard-removinginfrastructure suchas drainage)


Urban centres of developed countries and wealthysectors within cities of developing countries must play a vitalrole in reducing their carbon footprints. Their actions cannotbe reduced to technological fixes aimed at increasing energyefficiency and reducing the carbon intensity of cars, fabrics,utilities and other devices. Because goods, services, wastedisposal and transportation are aimed at satisfying urbanmarkets, the responsibility for the emissions produced intheir manufacture, production and energy expendituresneeds to be allocated to urban consumers, even when thesegoods and services are generated outside urban boundaries.This has very profound implications and difficulties for creat-ing real mitigation strategies. A call for a change inconsumption patterns and lifestyles away from a focus onmore and bigger is, clearly, fundamental.

Actions to induce changes in the factors shapingpopulation density, urban form, lifestyles, equity and othercomponents of urban development are equally fundamentalfor mitigation, adaptation and sustainable development.Transport strategies, for instance, need to be consistent withthe spatial structures of cities.

Urban development can also be a source of resilience.Population densities can create the potential for city-scalechanges in behaviour that can mitigate human impacts uponclimate and create opportunities for adaptation to floods,heat waves and other climate hazards. Properly designedinfrastructure developments can provide physical protection;well-designed communications and early warning systems;can help people to deal with disasters; and appropriate urbanplanning can help restrict the growth of populations andactivities in risk-prone areas.

Those urban centres with populations lower than500,000 people will be faced with great difficulties in copingwith the impacts of climate change, given their relatively lowmanagement capacity. However, they can also take advantageof their relatively small size to redirect their future growth inmore sustainable and resilient ways that reduce theiremission levels to a desired minimum and enhance theirresilience and ability to cope with climate hazards and otherstresses.

This Global Report is organized into seven chapters.Chapter 2 focuses on the international climate changeframework and the implications, opportunities andchallenges that it offers for urban action. It describes theprocess by which climate change became an internationalregime: the Climate Convention; the main mechanisms,instruments and financing strategies of the ClimateConvention; and the main positions of the parties to theKyoto Protocol. Aimed at providing policy-makers with anavigational tool to better steer a course through thecomplex universe of climate policy and action, the chapterpresents various components of the multilevel climatechange governance elaborated upon throughout the reportand describes the main actors, components and actions ofclimate governance at the international, supra-national(regional), national, and sub-national levels.

Chapter 3 examines the contribution of urban areasto climate change. It discusses the main protocols andmethods for measuring GHG emissions and examines trans-portation, industry, buildings and other sources of GHG

emissions in more detail. A summary of the scale of urbanemissions and how they vary between countries at differentstages of economic development is provided. The chapterillustrates how the total volume of emissions is stronglyshaped by such factors as a city’s geographic situation,demographic situation, urban form and density, andeconomic activities. It includes a discussion of both the mainfactors and underlying drivers influencing emissions.

Climate impacts and vulnerabilities are the main focusof Chapter 4. The chapter describes how climate change mayexacerbate the physical, social and economic challenges thatcities are currently experiencing. First describing the physi-cal climate change hazards facing urban centres, it goes on tolook at how the direct and indirect physical, economic andsocial impacts of these changes vary with disparities in exist-ing vulnerabilities within and across cities, identifyingspecific urban populations, regions and cities that are partic-ularly vulnerable to climate change and the reasons why thisis so. The chapter ends with concluding remarks on theimpact of climate change in cities and the lessons for policy.

Chapter 5 focuses on mitigation, one of the two mainresponses to climate change. It describes the mitigationpolicy responses and initiatives that are currently takingplace in cities in the areas of urban planning and infrastruc-ture development, transportation, the built environment andcarbon sequestration. It examines how such strategies andmeasures have been undertaken through different modesand mechanisms of governing (e.g. provision, regulation,self-governing and enabling), and explores the factorsshaping urban mitigation in institutional, economic, techni-cal and political terms (e.g. individual and institutionalleadership, knowledge and institutional capacity). Finally,the chapter provides a comparative analysis of emergingtrends in mitigation responses.

Chapter 6 looks at adaptation to climate change fromthe fundamental position that because the internationalcommunity has been unable to effectively respond to thechallenge of reducing GHGs to a level that would avoiddangerous interference with the climate system, adaptationresponses over the next decade will be critical. The chapterstarts by defining urban adaptation and adaptive capacity,followed by a review of some existing coping and adaptationexperiences by individuals, households, communities andurban governments, and then examines the relative rolesand potential partnerships between stakeholders, and looksat some mechanisms for financing adaptation.

Chapter 7 summarizes the key findings and messagesof the report, and proposes a set of integrating themes withrespect to urban areas facing climate change challenges. Thechapter first looks at the constraints and challenges to, andopportunities from, mitigation and adaptation actions, alongwith some of the linkages among drivers and vulnerabilities.It then goes on to highlight a variety of synergies and trade-offs between mitigation, adaptation and urban development.After briefly describing the current state of knowledge alongwith the gaps, uncertainties and challenges, the chapterprovides a series of suggestions on future policy directions interms of local, national and international principles andpolicies to support and enhance urban responses to climatechange.


Urban developmentcan … be a source ofresilience

Properly designedinfrastructure developments canprovide physicalprotection … andappropriate urbanplanning can helprestrict the growthof populations andactivities in risk-prone areas

Urban centres withpopulations lowerthan 500,000 people… can … takeadvantage of theirrelatively small sizeto redirect theirfuture growth inmore sustainableand resilient ways

1 UN, 2010.2 Due to increasing CO2

concentrations.3 The low-elevation coastal zone

is the contiguous area alongthe coast that is less than 10mabove sea level (IPCC, 2001b).

4 UN, 2010.5 UN, 2010.6 IPCC, 2007b; Satterthwaite et

al, 2007b, 2009c.7 UN, 2010.8 UN, 2010. See also Statistical

Annex, Table A.4.9 See Chapter 3 and Tables 3.5,

3.11 and 3.12.10 Dodman, 2009; Romero

Lankao et al, 2008, 2009a.11 McGranahan et al, 2005; Balk et

al, 2009.12 See UN-Habitat, 2007, p319.13 Le Treut et al, 2007.14 Ammann et al, 2007.15 Sabine et al, 2004.16 Sabine et al, 2004; Raupach et

al, 2007.17 Füssel, 2009.18 The data in this section are

derived from IPCC (2007d).

19 For a full list of gases to beassessed in national GHGinventories under the KyotoProtocol, see the note in Table3.1.

20 See Table 1.4; UN, 2010.21 IPCC, 2007d, p12.22 IPCC, 2007d.23 Examples include the Clinton

Foundation, Nicolas Stern, andMunich Insurance. SeeSatterthwaite, 2008a; Dodman,2009; and Chapter 4.

24 Satterthwaite, 2008a; Dodman, 2009.

25 Zhang, 2010.26 IPCC, 2007b.27 Alberti and Hutyra, 2009.28 Alber, 2010, p21.29 Romero Lankao, 2007a;

Satterthwaite, 2008a. See alsoChapter 3.

30 Brown et al, 2008.31 Ru et al, 2009.32 Satterthwaite, 2007; Romero

Lankao et al, 2005.33 See Chapter 3.34 Murphy, 2000; Gibbs, 2000.35 Roberts and Grimes, 1997.

36 See Chapter 3.37 Bin and Harris, 2006.38 Satterthwaite, 1997a;

McGranahan et al, 2001, p15;.39 Parry et al, 2007a; Wilbanks et

al, 2007; Satterthwaite et al,2007b; Romero Lankao et al,2008.

40 Räty and Carlsson-Kanyama,2010.

41 Satterthwaite, 2008a.42 Walker and Salt, 2006.43 Romero Lankao et al, 2009a.44 See Chapter 3.45 Other determinants of trans-

portation emissions are transitaccessibility, pedestrian friendli-ness and local attitudes andpreferences, which also influ-ence driving behaviour. Handyet al, 2005.

46 Marshall et al, 2005, p284.47 Vale and Campanella, 2005.48 This can be done through two

mechanisms: patterns of usethat do not overexploit localresources and go beyond thecarrying or absorbing capacityof local ecosystems; and the

ability and power to importresources from, or exportemissions to, surrounding andremote areas and to make upfor the impact (i.e. avoid localoverexploitation and pollu-tion). See Turner et al, 2003.

49 Allan Lavell, cited inSatterthwaite et al, 2007b.

50 Romero Lankao et al, 2009b.51 Moser, 2008; Moser and

Satterthwaite, 2010; Harlan etal, 2006; Romero Lankao andTribbia, 2009.

52 Alber, 2010.53 UN-Habitat, 2008c; Alber, 2010

(citing WIEGO and RealizingRights: The EthicalGlobalization Initiative, 2009).

54 UN-Habitat, 2008c.55 Alber, 2010.56 Bartlett, 2008.57 Bartlett, 2008, p1.58 Wolf et al, 2010.59 Satterthwaite et al, 2007b.60 Satterthwaite et al, 2007b.61 World Bank, 2009c, p1.


NOTES

Responses to the climate change challenge are taking placewithin the context of an international framework that shapesrelated actions and decisions at all levels.1 This framework isdefined here as the spectrum of agreements, mechanisms,instruments and actors governing and driving climate changeaction globally. The overall structure of this framework is complex and multidimensional in that it is comprised of elements that are quite different and distinct in many of their functions and approaches, constituencies, scope and focus.2 While international agreements negotiated by national governments such as the United NationsFramework Convention on Climate Change (UNFCCC) andits Kyoto Protocol remain crucial aspects of the framework,they are not the only mechanisms governing climate changeaction. Other layers of intervention have become equallyimportant in implementing innovative climate changeresponses and policies, including those at the regional, sub-national and local levels.

Cities have a vital role to play in the implementationand achievement of commitments within the internationalclimate change framework. They also stand to benefit fromthe opportunities created by this framework for localresponses to climate change. Yet, local-level actors andauthorities often lack an understanding of the nature andfunctioning of the various components of the internationalclimate change framework and how they could utilize theseto enhance their mitigation and adaptation strategies. Forinstance, many decision-makers operating at the city levellack a working knowledge of the opportunities andconstraints associated with international financing options,including those established as part of the UNFCCC.3 In viewof this, the aim of this chapter is to highlight the keyelements of the international climate change framework andits effects on interventions at the local level. It is alsointended to frame discussions of climate change conditions,trends and policies in the rest of this Global Report.

The chapter starts by briefly describing the process bywhich climate change emerged as an issue of internationalconcern culminating in the establishment of the UNFCCC asthe key element of the international regime governingclimate change issues. The core mechanisms, instrumentsand financing strategies of this Convention are thenoutlined. The Kyoto Protocol is also reviewed as the main

international treaty with legally binding emission reductioncommitments. Subsequently, the key actors, componentsand actions of climate governance at the international,regional, national and sub-national levels are considered.Finally, the implications of the international climate changeframework for local action at the city level are outlined.

THE UNITED NATIONSFRAMEWORK CONVENTIONON CLIMATE CHANGEClimate change issues have been discussed since the early19th century (see Table 2.1), but only emerged as an inter-national policy concern during the 1970s and 1980s whentechnological advances allowed scientists to state with morecertainty that atmospheric concentrations of greenhousegases (GHGs) were on the rise and that this could haveprofound ramifications for the Earth’s climate. Between1988 and 1990, national governments began to play agreater role in defining the climate change agenda, and theIntergovernmental Panel on Climate Change (IPCC) wasestablished in 1988 to provide them with information onglobal warming trends through regular scientific assessments(see Box 2.1).

The process of formally negotiating an internationalclimate change treaty started in December 1990, when the United Nations General Assembly created the Inter-governmental Negotiating Committee for a FrameworkConvention on Climate Change. In 1992, the committeeadopted the United Nations Framework Convention onClimate Change (UNFCCC) at the United NationsHeadquarters, New York. The UNFCCC, also known as theClimate Convention, entered into force in 1994 and hadbeen ratified by 193 countries by October 2010.4 Theultimate objective of the Convention is to stabilize globalgreenhouse gas (GHG) concentrations at a level that wouldprevent human interference with the climate system.5 TheConvention also aims to assist countries, especially develop-ing ones, in their efforts to adapt to the effects of climatechange.

The Convention’s efforts to curb emissions arepremised on some explicit and implicit norms which have

Local-level actorsand authoritiesoften lack an understanding of the nature and functioning of thevarious componentsof the internationalclimate changeframework

C H A P T E R

CITIES AND THE INTERNATIONALCLIMATE CHANGE FRAMEWORK

2

become fundamental to the international climate regime.Chief among these are the principle of ‘common but differ-entiated responsibilities and respective capabilities’ and the‘precautionary principle’.6 The first recognizes historicaldifferences in the contribution of developed and developingcountries to climate change, as well as differences in their

respective economic and technical capacity to tackle theseproblems.7 In this regard, the Convention places the greatestresponsibility for fighting climate change on developedcountries, given their role in generating much of the GHGemissions in the past. The second implies that even in theabsence of full scientific certainty, countries are obliged to

The IPCC’s assessment processis a vital interfacebetween science andpolicy and a crucialmechanism bywhich scienceinforms policy-making


Table 2.1

Major milestones ininternational climatechange governance

1827 French scientist Jean-Baptiste Fourier is the first to consider the ‘greenhouse effect’ – the phenomenon whereby atmospheric gases trap solar energy,increasing the Earth’s surface temperature.

1896 Swedish chemist Svante Arrhenius blames the burning of fossil fuels producing CO2, the main greenhouse gas, for contributing to climate change.1950s Global warming science grows with increasing information on the impacts of greenhouse gases upon the world’s climate, together with the develop-

ment and growth of environmental movements.1979 First World Climate Conference in Geneva, Switzerland, calls on governments to forecast and prevent potential human-made changes in climate.1988 The Intergovernmental Panel on Climate Change (IPCC) is established to produce regular scientific and technical assessments of climate change.1992 The United Nations Framework Convention on Climate Change (UNFCCC) is adopted in New York, US, on 9 May 1992, and enters into force on 21

March 1994.1997 The Kyoto Protocol to the Convention is adopted at COP-3 in Kyoto, Japan, and enters into force on 16 February 2005.2001 The Marrakesh Accords, a set of detailed rules for the implementation of the Kyoto Protocol, is adopted during COP-7 in Marrakesh, Morocco.2007 Negotiations for a new international treaty to take over from the Kyoto Protocol in 2012 begin in Bali, Indonesia, during COP-13. The Bali Road Map,

a two-year process to finalize a binding agreement in 2009 during COP-15, is agreed upon.2009 The main outcome of COP-15, the Copenhagen Accord, is a non-binding agreement which seeks to cap the global temperature rise and raise finances

for climate change action in developing countries.2010 The Cancún Agreements are adopted during COP-16 in Cancún, Mexico, containing a package of decisions on mitigation and adaptation targets,

implementation and funding.2011 COP-17, Durban, South Africa, 28 November–9 December 2011.

Sources: Baumert et al, 2005; ICLEI et al, 2009; New Scientist, 2009

Box 2.1 The Intergovernmental Panel on Climate Change

Sources: IPCC, undated a, undated b; UN, 1988; Brasseur et al, 2007

The IPCC was created in 1988 by the World MeteorologicalOrganization (WMO) and the United Nations EnvironmentProgramme (UNEP) in order to keep world governments informedof climate change issues. The IPCC’s 194 member countries meetonce a year during sessions also attended by numerous other insti-tutions and observer organizations.

The United Nations General Assembly resolution 43/53 of6 December 1988 states that the role of the IPCC is to ‘provideinternationally coordinated scientific assessments of the magnitude,timing and potential environmental and socio-economic impact ofclimate change and realistic response strategies’. The same resolu-tion requested the WMO and UNEP to initiate a comprehensivereview and subsequent development of recommendations withrespect to the following vis-à-vis the IPCC:

• the state of knowledge of the science of climate and climaticchange;

• programmes and studies on the social and economic impact ofclimate change, including global warming;

• possible response strategies to delay, limit or mitigate theimpact of adverse climate change;

• the identification and possible strengthening of relevant exist-ing international legal instruments having a bearing on climate;and

• elements for inclusion in a possible future internationalconvention on climate.

The IPCC analyses scientific and socio-economic information onclimate change and its impacts, and assesses options for mitigation

and adaptation. It provides scientific, technological, and socio-economic findings to the Conference of the Parties (COP) to theUNFCCC. The IPCC’s assessment process is a vital interfacebetween science and policy and a crucial mechanism by whichscience informs policy-making. Accordingly, the IPCC has played acrucial role in establishing the importance of the climate changeissue; providing an authoritative resolution of policy-relevant scien-tific questions; demonstrating the benefits and costs of variouspolicy options; identifying new research directions; and providingtechnical solutions.

To date, the IPCC has prepared comprehensive scientificreports on climate change on a regular basis. The First AssessmentReport of the IPCC (published in 1990) indicated that levels ofhuman-made GHGs were increasing in the atmosphere andpredicted that these would exacerbate global warming. It also illus-trated the need for a political platform for countries to tackle theconsequences of climate change, thereby playing a critical role inthe creation of the UNFCCC. Both the Second (1995) and Third(2001) Assessment Reports implied stronger linkages betweenhuman activity and climate change, thereby strengthening efforts forthe negotiation of the Kyoto Protocol. The Fourth (and latest)Assessment Report (2007) noted that the evidence for globalwarming is ‘unequivocal’ and forecasted warming of 1.8 ºC to 4.0ºCby 2100. The IPCC is currently working on the Fifth AssessmentReport, which is due to be released in 2014.

In addition to the assessment reports, the IPCC hasprepared numerous other reports, methodologies and guidelines tosupport countries in implementing their commitments.

anticipate, prevent or minimize the causes of climate changeand mitigate its adverse effects.8

Countries ratifying the treaty are referred to as‘Parties to the Convention’ and agree to develop nationalprogrammes to slow climate change. ‘Annex I’ countriesinclude developed countries that were members of theOrganisation for Economic Co-operation and Development(OECD) in 1992 and also countries with economies in transi-tion. These countries are required to provide regularinventories of their GHG emissions using 1990 as the baseyear for these tabulations.9 ‘Annex II’ countries consist ofAnnex I countries excluding countries with economies intransition. These parties are expected to support mitigationand adaptation activities in developing countries financiallyand through the transfer of technology. ‘Non-Annex I’countries are developing countries and are given specialconsideration due to their limited capacity to respond toclimate change.10

The main authority of the Convention is the‘Conference of the Parties’ (COP), which is comprised of allparties and meets annually to assess ‘progress made byParties in meeting their commitments and in achieving theConvention’s ultimate objectives’.11 Sessions of the COP, ofwhich 16 have taken place (by the end of 2010) since theConvention entered into force in 1994, serve as the mainforums for negotiations between the parties and theadoption of key decisions and resolutions. This is particularlyimportant since the Convention mostly contains generalformulations that are deliberately ambiguous to accommo-date the diverse positions of the parties. The COPs are alsoattended by a large number of observers, including intergov-ernmental, non-governmental and other civil societyobservers.12

The first Conference of the Parties (COP-1) took placein December 1995 in Berlin, Germany, and expressedconcern about the ability of countries to meet theiremissions targets and commitments. Through the BerlinMandate adopted at this meeting, a committee was estab-lished to negotiate a protocol on climate change by 1997,including additional GHG emissions reduction commitmentsfor developed countries for the post-2000 period.13 By thetime COP-2 took place in July 1996 in Geneva, Switzerland,consensus on the negotiation of a protocol was not yet insight and preliminary national communications suggestedthat countries were unlikely to meet their emissions reduc-tion targets (i.e. to return to their 1990 emissions levels by2000).14 However, the meeting endorsed the SecondAssessment Report of the IPCC, and reaffirmed the need forlegally binding ‘quantified emission limitation reductionobjectives’.15 In 1997, the principles under the UNFCCCwere finally translated into legally binding commitmentsthrough the Kyoto Protocol, which was adopted at COP-3 inKyoto, Japan.16

In addition to its focus on emissions reduction, theUNFCCC also seeks to support adaptation activities in devel-oping countries. Accordingly, in 2001, during COP-7 inMarrakesh, Morocco, three main funding mechanisms foradaptation were set up under the UNFCCC – namely, theSpecial Climate Change Fund, the Least Developed

Countries Fund and the Adaptation Fund (see Box 2.2).These are administered by the Global Environment Facility(GEF), an international partnership between 182 countries,international institutions, non-governmental organizations(NGOs), and the private sector to address global environ-mental challenges. The GEF was established in 1991 as apilot programme at the World Bank with UNEP and theUnited Nations Development Programme (UNDP) as imple-menting partners. During the United Nations Conference onEnvironment and Development (UNCED) in 1992, it wasrestructured to become a separate institution and the mainentity managing the funding mechanisms of the UNFCCC.17

A key challenge for the UNFCCC is that its main goalis somewhat ‘indeterminate’. In other words, although itconveys the long-term goal of reducing emissions, itcautiously avoids any quantitative expression of it.18 This ispartly because the climate domain is characterized by uncer-tainties regarding causes, impacts and relationships.Although the publication of the IPCC’s Fourth AssessmentReport in 2007 signalled that the scientific community hasestablished with greater clarity that human activities are themain causal factors of the unprecedented changes in ourclimate system, climate science still faces challenges. Forinstance, it cannot currently help policy-makers to know,with absolute certainty, how much is too much (e.g. what isthe point beyond which emissions are too high). Science alsocannot objectively ascertain at what level human interfer-ence with climate becomes dangerous. Some form of valuejudgement is unavoidable. And value judgements are contextspecific, not only because climate impacts differ from placeto place, but also because different people perceive the risksin diverse ways.19

A key challenge forthe UNFCCC is thatits main goal issomewhat ‘indeterminate’

19Cities and the International Climate Change Framework

Box 2.2 Funding mechanisms of the UNFCCC

The Special Climate Change Fund is intended to finance activities related to adaptation, technol-ogy transfer and capacity-building, energy, transport, industry, agriculture, forestry, wastemanagement and economic diversification. By September 2009, voluntary contributions ofaround US$120 million had been pledged for the fund and 24 projects had been approved.a

The Least Developed Countries Fund aims to assist 48 least developed countries toprepare and implement National Adaptation Programmes of Action (NAPAs) through whichthey identify priority adaptation activities for funding.b The rationale for this fund lies in therecognition of the limited ability of such countries to adapt to the consequences of climatechange.c By March 2010, the United Nations Framework Convention on Climate Change(UNFCCC) had received NAPAs from 44 countries.d As of 30 September 2009, US$180 millionhad been pledged for this fund through voluntary contributions and, by 2010, 84 projects hadbeen approved.e

The Adaptation Fund was established to finance adaptation projects and programmes indeveloping countries that are especially vulnerable to climate change impacts.f It is to be fundedfrom a 2 per cent levy on all Clean Development Mechanism (CDM) project activities (see Box2.3). The fund only became operational in 2010 and by October 2010, projects had beenapproved in only four countries – namely, the Solomon Islands, Nicaragua, Senegal and Pakistan.g

Although the fund is expected to have grown to US$500 million by 2012, this falls short of theestimated US$50 billion required annually for adaptation activities in developing countries.h

Sources: a Climate Fund Update, undated a; UNFCCC, undated f; GEF, undated; World Bank, 2009b; b UNFCCC, undated g; c UNFCCC, undated h; d UNFCCC, undated i; e Climate Fund Update, undated b; GEF, undated; World Bank, 2009b; f Climate Fund Update, undated c; UNFCCC, undated j; g AlertNet, 2010a, 2010b; h IIED, 2009

The Kyoto Protocol… is a bindingagreement whichcommits developedcountries to stabilizetheir GHG emissions


Furthermore, because many of the cause-and-effectrelationships are long and potentially irreversible, theyrequire planning that goes beyond the tenure and even thelifetime of most current decision-makers and stakeholders.Complex interdependencies exist between different policyareas within and beyond climate policy, and the internationalcommunity may fail to put in place the unprecedented seriesof response mechanisms that are required.20 The difficultiesrelated to international climate change negotiations (i.e.stalled negotiations during most of the COPs followed bylast-minute key decisions by some parties) further complicatethe operationalization and implementation of the UNFCCC.

THE KYOTO PROTOCOLThe Kyoto Protocol was adopted on 11 December 1997 inKyoto, Japan, during COP-3, and entered into force on 16February 2005. By the end of 2010, the protocol had beenratified by 191 countries.21 While the protocol holds incommon the objective and institutions of the UNFCCC, thetwo differ in that the protocol is a binding agreement whichcommits developed countries to stabilize their GHGemissions, while the Convention only encourages thesame.22 Key decisions and resolutions on the implementationof the Kyoto Protocol’s provisions are taken during theMeeting of the Parties to the Kyoto Protocol (MOP), which

occurs in conjunction with the meetings of the COP to theUNFCCC.23 The rules for implementing the protocol werespelt out in the Marrakesh Accords adopted in 2001 at COP-7 in Marrakesh, Morocco.24

According to the protocol, developed countriescommit to reduce their overall GHG emissions by at least 5per cent below 1990 levels during the commitment periodfrom 2008 to 2012.25 They submit annual emission invento-ries and national reports at regular intervals and a comp-liance system is in place to assist countries to meet theirtargets. Some developed countries rejected the protocol butare developing alternative regulatory approaches.26 Devel-oping countries have also ratified the protocol but do notneed to limit or reduce their emissions. In addition to reduc-ing emissions, the Kyoto Protocol also seeks to assistvulnerable developing countries to adapt to the adverseeffects of climate change, primarily through the AdaptationFund (see Box 2.2). During COP-16 (in Cancún, Mexico) adecision on binding emissions targets for a ‘second commit-ment period’ (i.e. beyond 2012) was deferred to a futuredate.

Before its adoption, negotiations of the Kyoto Protocolwere stalemated over two critical issues. First, developedcountries were in disagreement regarding mitigation targets.The European Union (EU) supported a 15 per cent reductionin GHG emissions below 1990 levels; the US and Australiaproposed lower targets; and Japan’s position was somewherein the middle. To deal with these differences, diverseemissions targets were set, ranging from a 10 per centincrease for Iceland to an 8 per cent reduction for Germany,Canada and other countries.27 Rather than being based onwhat the scientific community would consider necessary tostabilize emissions at current levels, or reflecting the levelsof reductions that countries could achieve, emissions targetswere the outcome of tough bargaining in closed-doorsessions between representatives of the US, the EU andJapan during the final hours of COP-3 in Kyoto, Japan.28

Second, the flexibility of implementation mechanismswas an issue of contention. While developing countries andthe EU supported domestic action as the main means toachieve emissions reduction targets, the US and some indus-tries (mostly from the energy sector) argued that developedcountries could achieve their targets through emissions-abatement projects in other countries or through emissionstrading. Thus, although countries are expected to meet theirmitigation targets primarily through national programmes,the Kyoto Protocol enables them to cut their emissionsthrough three flexible mechanisms – namely, the CleanDevelopment Mechanism (CDM), joint implementation andemissions trading (see Box 2.3).

Despite already contributing to emissions reductionsglobally, the flexible mechanisms have also been criticized.For instance, CDM has been criticized for simply movingemission reduction activities and their socio-economic andenvironmental impacts to where it is cheapest to make them,which normally means a shift from developed to developingcountries.29 Also, the CDM is not necessarily able to deliverthe promised development dividends to the host country.30

Emissions trading has been critiqued for allowing developedcountries to earn emissions reduction credits primarily

Box 2.3 Flexible mechanisms under the Kyoto Protocol

The three flexible mechanisms of the Kyoto Protocol are as follows:

1 Emissions trading allows developed countries that exceed their target emissions to offsetthem by buying ‘credits’ from countries that stay below their emission targets. Emissionquotas were agreed with the intention of reducing overall emissions by developedcountries by 5 per cent of the 1990 levels by the end of 2012. For the five-year complianceperiod from 2008 until 2012, countries that emit less than their quota will be able to sellemissions credits to countries that exceed their quota.a In 2010, the value of the globalcarbon market was estimated to be worth a staggering US$144 billion.b

2 The Clean Development Mechanism (CDM) – which has been operational since 2006 –enables emission reduction projects in developing countries to earn certified emissionreduction credits, which can then be traded or sold. These credits can be purchased bydeveloped countries to achieve a twofold purpose: to meet their own emissions reductiontargets under the Kyoto Protocol and to assist other countries in achieving sustainabledevelopment through climate change mitigation.c CDMs have registered an astoundinggrowth, with over 5000 projects in the pipeline as of August 2010.d

3 Joint implementation allows developed countries to invest in emissions reduction activitiesin other developed countries. A developed country can thus earn emission reduction unitsfrom an emission reduction or emission removal project in another developed country,which can be counted towards meeting its Kyoto target.e A total of 243 joint implementa-tion projects were in the pipeline as of 1 November 2009.f

Transactions by parties to the Kyoto Protocol under the above three flexible mechanisms aretracked and recorded through an international transaction log.g The log monitors the compli-ance of transactions with the rules of the Kyoto Protocol and may reject entries where this isnot the case. Between 1 November 2008 and 31 October 2009, a total of 225,119 transactionproposals were submitted to the international transaction log.

Sources: a UNFCCC, undated q; b World Bank, 2010b; c UNFCCC, undated m; d CD4CDM, undated; e UNFCCC, undatedn; f Gilbertson and Reyes, 2009; g UNFCCC, undated l

through trading rather than through cutting their domesticemissions. It also encourages developed nations to avoidtheir obligation to develop pollution reduction innovations toenable developing countries to increase production whilelimiting pollution.31

In an effort to create a framework of action for theperiod after the end of the current commitment period ofthe Kyoto Protocol in 2012, the Bali Road Map was adoptedin 2007 during COP-13 to finalize a binding agreement in2009 during COP-15 in Copenhagen, Denmark. However(and as was the case with the negotiations within both theUNFCCC and the Kyoto Protocol, and despite two years ofadvance work initiated by the Bali Road Map), little progresswas made during two weeks of negotiations in Copenhagen.With time running out, the US forged the CopenhagenAccord, a ‘non-binding’ agreement that all but a handful ofparties accepted. While the Copenhagen Accord succeededin forging agreement on the need to address climate change,it is viewed as a major compromise that emerged due to thefailure of countries to agree on a binding agreement togovern emissions reduction in the post-Kyoto period.

In contrast, the latest meeting, COP-16 in 2010(Cancún, Mexico) has been dubbed a ‘beacon of hope’ thathas restored faith in international climate change negotia-tions. While an agreement for the post-Kyoto period was notreached, the adoption of the ‘Cancún Agreements’, apackage of decisions on adaptation and mitigation targets,implementation and funding, has managed to ebb some ofthe pessimism that emerged following COP-15. In additionto encouraging countries to push their emissions reductiontargets over and above the commitments within the KyotoProtocol, the Cancún Agreements establish mechanismssuch as the Green Climate Fund, the Cancún AdaptationFramework and the Climate Technology Centre and Networkto strengthen climate change action.32

The next Conference of the Parties will take place in2011 (28 November to 9 December in Durban, SouthAfrica) and an attempt to forge a binding agreement for thepost-2012 period will once again be made. However, itremains uncertain whether the international community willbe able to reach a legally binding agreement to replace theKyoto Protocol. The continued delay in reaching such anagreement is expected to have serious negative conse-quences for global emissions reduction efforts.33

Despite its significance as the main binding agree-ment between parties, the Kyoto Protocol has been criticizedon a variety of grounds. Some argue that it imposes highburdens on developed countries, while others suggest that itprovides ineffective incentives for participation and compli-ance. Yet others point out that it creates modest short-termclimate benefits while failing to provide a long-term solution.Indeed, numerous alternatives to the protocol have beensuggested to address these shortcomings.34 The existence ofa set of initiatives parallel to the Kyoto Protocol is a sign ofthe fragmented nature of the international climate changeframework and has led to an extensive debate on how tocontinue the negotiation of future treaties. The majority ofpolicy proposals still support a universal framework ofclimate governance, while other recent proposals implicitly

create the possibility of further institutional fragmentation ofthis framework (e.g. starting a bottom-up process in whichcountries would put on the table acceptable measures in linewith national circumstances).35

OTHER CLIMATE CHANGEARRANGEMENTSAlthough international climate change negotiations betweennational governments remain crucial, the last two decadeshave witnessed the multiplication of other regional, nationaland local (e.g. city) mechanisms and actors responding to theclimate challenge. These include initiatives of multilateraland bilateral entities, sub-national tiers of government, grass-roots groups, private enterprises, NGOs and individuals. Thissection describes the role of these in curbing GHG emissions(mitigation) and in climate change adaptation. Furthermore,it examines the levels at which these actors operate andoutlines some of the actions, initiatives and instruments thatthey have developed and implemented to date.

International level

A number of actors are actively developing strategies forclimate change adaptation and mitigation at the internationallevel, including the United Nations, multilateral and bilateralagencies. These initiatives are mostly designed to supportthe implementation of the commitments of the KyotoProtocol as the main international treaty for climate change.Although a multitude of international actors are currentlyactive in responding to climate change, many of their strategies, programmes and actions have evolved in isolationfrom each other. The lack of a clear division of responsibili-ties between the numerous international actors has led insome cases to overlapping functions, conflicting mandatesand blurred objectives, and in other cases to constructivecollaboration.36 In turn, this has implications for the extentto which city authorities are able to make use of interna-tional funds and programmes to implement local adaptationand mitigation initiatives.

n The United NationsThe United Nations is one of the key climate change actorsat the international level. In addition to its work through theUNFCCC and the IPCC described earlier, a number of itsprogrammes and other entities are contributing to the globalresponse to climate change. Since 2007, the UN hasembarked on an initiative to ensure better coordination of itsresponse to climate change. Towards this end, five focusareas were defined and convening UN entities identified foreach focus area (see Table 2.2). Some additional cross-cutting areas were also identified, including climate scienceand knowledge and public awareness.37 This approach isintended to minimize duplication of activities across variousentities, thereby making the UN’s work on climate changemore effective and efficient.

UNEP is one of the organizations which has played a pivotal role in action on climate change, having jointly


It remains uncertainwhether the internationalcommunity will beable to reach alegally bindingagreement toreplace the KyotoProtocol

The UN hasembarked on aninitiative to ensurebetter coordinationof its response toclimate change

established the IPCC with the World MeteorologicalOrganization (WMO) in 1988 and actively engaged withadaptation and mitigation efforts since then.38 In addition toa wide range of activities on the urban environment, UNEPis also implementing climate change-related activitieswithin the context of cities through its Campaign on Citiesand Climate Change. This campaign aims to enable cities tofruitfully engage in the global climate debate and reducetheir GHG emissions.39

The WMO – which is the UN specialized agency forweather, climate, hydrology and related environmentalissues – has led the process of generating scientific evidenceand knowledge on climate change trends and has been theprincipal provider of the information underlying the IPCC’sassessment reports (see Box 2.1). The WMO has also beenissuing ‘annual statements on the status of the globalclimate’ to document extreme weather events and provide ahistorical overview of climate variability.40

As the agency with a mandate to foster sustainableurbanization, the United Nations Human SettlementsProgramme (UN-Habitat) is well positioned to addressclimate change issues specifically within the urban context.In 2008, UN-Habitat launched its Cities and Climate ChangeInitiative to enhance the adaptive capacities and responsive-ness of local governments in developing countries to climatechange, as well as to support their efforts at reducing green-house gas emissions (see Box 2.4).

Different UN entities have also been collaborating inthe area of climate change. A case in point is the joint estab-lishment of the United Nations Collaborative Programme onReducing Emissions from Deforestation and Forest Degrad-ation in Developing Countries (UN-REDD) in 2008 by UNEP,UNDP and the Food and Agriculture Organization (FAO).41

Furthermore, UN agencies frequently implement climatechange activities jointly with a number of partners outsidethe UN system. One example is the collaboration betweenUN-Habitat, UNEP and the World Bank to establish theInternational Standard for Determining Greenhouse GasEmissions for Cities, a common standard for measuringemissions from cities (see Box 2.5).42

The UN has also been playing a leading role in termsof disaster risk management, which is fundamental toclimate change adaptation efforts. The International Strategyfor Disaster Reduction (UNISDR), which was adopted in2000, is a system of partnerships between local, national,regional and international organizations with the overallobjective of supporting global disaster risk reduction.UNISDR functions as the United Nations focal point for thecoordination of disaster reduction. It is also tasked tomobilize political and financial commitments to implementthe Hyogo Framework for Action 2005–2015, the maininternational agreement which lays out principles and priori-ties for global disaster risk reduction action, though it is notlegally binding.43 The ‘urban agenda’ is receiving greaterattention in the work of the UN on disaster issues, with theUNISDR launching a campaign on Making Cities Resilient:My City is Getting Ready in 2010 to urge mayors and localgovernments to commit to making their cities more resilientto disasters, including those related to climate change.44

On the whole, the UN has been performing a crucialrole in steering and coordinating climate change action inter-nationally. It has also been at the forefront of generatingscientific knowledge on climate change to support interna-tional negotiations and evidence-based policy-making. Theinitiative to harmonize the work of various UN entities on

UN-Habitat is wellpositioned toaddress climatechange issues specifically withinthe urban context


Table 2.2

Focus areas for acoordinated UnitedNations response toclimate change

Focus area Convening United Nations entities

Adaptation High-level Committee on Programmes of the Chief Executive Board of the United NationsTechnology transfer United Nations Industrial Development Organization (UNIDO) and United Nations Department for Economic and

Social Affairs (UNDESA)Reduction of emissions from United Nations Development Programme (UNDP), the Food and Agricultural Organization (FAO) and the United deforestation and degradation Nations Environment Programme (UNEP)(REDD)Financing mitigation and UNDP and the World Bank groupadaptation actionCapacity-building UNDP and UNEP

Source: UN, 2008

Box 2.4 UN-Habitat’s Cities and Climate Change Initiative

Launched in 2008, the Cities and Climate Change Initiative (CCCI) seeks to promote collabora-tion between local governments and their associations and partners on climate change-relatedtopics, enhance policy dialogue between local and national governments on addressing climatechange, support local governments in addressing climate change impacts while reducing green-house gas (GHG) emissions, and foster awareness, education and capacity-building for theimplementation of climate change policies and strategies.

CCCI initially helped four pilot cities in Asia, Africa and Latin America to carry outclimate change assessments. These cities already are at risk of natural disasters. In Esmeraldas(Ecuador), for example, more than half the population live in areas at risk of floods orlandslides, while in 2006 two typhoons hit Sorsogon City (the Philippines), destroying some10,000 homes. Climate change will only exacerbate those vulnerabilities in the 21st century.CCCI currently plans to help those cities deepen their assessments in priority areas, developclimate change strategies and action plans, mainstream findings into ongoing planning processes,and build capacity. At the same time, CCCI has been expanding to include five new cities inAfrica in 2009 (Bobo Dioulasso, Burkina Faso; Mombasa, Kenya; Walvis Bay, Namibia; Kigali,Rwanda; and Saint Louis, Senegal) and nine new cities in Asia and the Pacific in 2010 (Batticaloaand Negombo, Sri Lanka; Kathmandu, Nepal; Ulaanbaatar, Mongolia; Pekalongan, Indonesia; PortMoresby, Papua New Guinea; Lami City, Figi; Apia, Western Samoa; and Port Vila, Vanuatu).

CCCI also is developing capacity-building tools to help cities access carbon finance orto develop climate change plans, drawing on local experiences. Finally, CCCI is taking lessonsthat it has captured through its local-level work, and disseminating and applying them globally.For example, the recent experiences of Negombo (Sri Lanka) in determining a baseline for itsGHG emissions are helping to inform the next iteration of the International Standard forDetermining Greenhouse Gas Emissions for Cities (see Box 2.5).

Source: UN-Habitat, 2009b

climate change since 2007 is expected to further consolidatethe organization’s leading role in guiding the global responseto climate change.

n Other multilateral organizationsOther multilateral institutions are playing an increasinglyimportant role in climate change adaptation and mitigationat various levels. For instance, although it was thought thatclimate considerations were marginal for multilateral devel-opment banks in the past, this has been changing in recentyears.45 The World Bank Group is one such actor that hasbeen reinforcing its engagement with climate change issues(see Box 2.6). This includes working directly on climatechange issues within the urban context. The World BankInstitute is implementing city-focused climate change activi-ties specifically in four areas: South–South learning betweencities; city-level networks and knowledge platforms; knowl-edge exchange and structured learning; and customizedsupport to selected cities.46 Furthermore, under its CarbonFinance Assist Programme, which aims to enhance the capacity of developing countries to engage fully with theflexible mechanisms of the Kyoto Protocol (see Box 2.3), theWorld Bank has further initiated a twinning initiative forclimate change knowledge-sharing between cities and aCarbon Finance Capacity Building programme for emergingmegacities.47 This programme seeks to promote the role ofcarbon finance for sustainable urbanization and povertyreduction.48 In addition, in 2009, the World Bank estab-lished a Mayors’ Task Force on Urban Poverty and ClimateChange during COP-15 in Copenhagen, Denmark, andintends to prepare a Mayor’s Handbook on Adaptation.49

The regional development banks are also key multilat-eral actors responding to climate change. In 2007, the AsianDevelopment Bank established the Clean Energy FinancingPartnership Facility to enhance energy security and to abateclimate change in developing member countries. Potentialinvestments under this facility include those related todeveloping and promoting clean energy technologies, includ-ing for low-income groups. By 2010, the funds for thisfacility had reached US$44.7 million.50 In 2009, the Inter-American Development Bank launched the SustainableEnergy and Climate Change Fund with a total annual contri-bution of US$20 million. The fund aims to supportsustainable energy initiatives and innovations, as well asresponses to climate change in Latin America and theCaribbean.51 Elsewhere, the European Investment Bank,whose lending activities focus mainly on EU member states,has been a key player in supporting climate changeresponses through mitigation, adaptation, research, develop-ment and innovation, technology transfer and cooperation,and support for carbon markets.52

The OECD is another multilateral organization whichhas been working on climate change issues for almost threedecades, particularly on economic and policy analysis. Withrespect to climate change issues in cities, the OECD aims tosupport climate-sensitive local and regional developmentpolicies. Accordingly, it has published a number of reports onthis subject analysing the linkages between climate changeand urban development.53 The organization intends to

continue its work on climate change in the urban contextwith a focus on the impacts of green growth and the effect ofurban spatial form on GHG emissions.54

In sum, multilateral actors are playing an increasinglyimportant role in supporting climate change responses. Theyhave especially become a prominent source of financial andtechnical assistance for climate change action in developingcountries.


Box 2.5 International Standard for Determining Greenhouse Gas Emissions for Cities

Introduced in March 2010, the International Standard for Determining Greenhouse GasEmissions for Cities seeks to establish a common standard for measuring emissions from cities.In addition to emissions generated within urban areas, the standard also measures emissionsgenerated outside urban boundaries that are driven by urban-based activities. This includes thefollowing:

• out-of-boundary emissions from the generation of electricity and district heating whichare consumed in cities (including transmission and distribution losses);

• emissions from aviation and marine vessels carrying passengers or freight away from cities;and

• out-of-boundary emissions from waste that is generated in cities.

Rather than attributing the responsibility for emissions to local governments, the standardseeks to illustrate the extent to which the urban economy is carbon dependent. Accordingly,emissions from the generation of power for consumption in cities, from city-bound aviation andmarine transport, and from waste generated in cities are included. Furthermore, standardizedreporting will help cities to benchmark themselves.

Source: UNEP et al, 2010

Box 2.6 Climate change initiatives at the World Bank

Some of the major climate change activities at the World Bank during recent years include thefollowing:

• In 2005, the Clean Energy Investment Framework was created to accelerate clean energyinvestments in developing countries. The framework functions as a collaborative endeav-our between multilateral development banks and countries to identify investments neededto accelerate the transition to a low-carbon economy and support adaptationprogrammes.

• In 2008, a Strategic Framework was prepared to guide the World Bank’s work on climatechange issues with a focus on the following six action areas: supporting climate actions incountry-led development processes; mobilizing additional finance; facilitating the develop-ment of market-based financing mechanisms; leveraging private-sector resources;supporting the development and deployment of new technologies; and enhancing policyresearch, knowledge and capacity-building.

• In 2008, the Climate Investment Fund was launched with pledges of US$10 billion from tendonor countries to fund the demonstration, deployment and transfer of low-carbonprogrammes to developing countries. There are two main funds under this initiative –namely, the Clean Technology Fund for activities related to the power sector, transportand energy efficiency; and the Strategic Climate Fund to support pilot approaches with thepotential for scaling up. The latter focuses on key areas of relevance to climate changemitigation in cities, including energy efficiency in buildings and industry.

Sources: World Bank, undated b; UNCTAD, 2009; Climate Investment Funds, undated

n Bilateral organizationsA number of bilateral initiatives to address climate changehave emerged over the past few years, although less atten-tion has been given to financial flows emanating from theseinitiatives.55 For instance, one of the largest funds of thistype is Japan’s Cool Earth Partnership, established to supportclimate change mitigation and adaptation, as well as accessto clean energy in developing countries for the period of2009 to 2013. The fund is worth US$10 billion, with thebulk of it (80 per cent) allocated for activities related to thereduction of GHG emissions rather than adaptation. Anothersuch fund is the UK’s Environmental Transformation Fund –International Window, launched in 2008 to support develop-ment through environmental protection and climate changeadaptation in developing countries. US$1.6 billion was madeavailable for this fund. The International Climate ProtectionInitiative of Germany, launched in 2008, is a mechanism forfinancing climate change projects and is funded from thesale of emissions certificates. The focus is on developing,newly industrializing and transition countries. Since 2008,181 projects worth a total of €354 million have beenlaunched.

The EU, another major bilateral actor, works onclimate change issues mainly through the Global ClimateChange Alliance, an initiative launched in 2007 to support,through direct financial and technical assistance, adaptationand mitigation activities mainly in the least developedcountries and the small island developing states. The alliancealso seeks to strengthen dialogue between these countriesand the EU on climate change issues in the context of inter-national negotiations.56 The EU earmarked an initial €90million for the work of the alliance between 2008 and2010.57 The work of the alliance is organized around fivepriority areas – namely, adaptation; reducing emissions fromdeforestation and degradation; enhancing the participationof developing countries in CDMs; promoting disaster riskreduction; and mainstreaming climate change into povertyreduction strategies.58

While bilateral funds such as the ones describedabove are actively supporting climate change responses indeveloping countries, most are considered to be part ofdonors’ official development assistance. Questions havearisen as to whether this is the best approach for bilateralassistance and whether traditional development aid agenciesare best placed to dispense such funds. Furthermore, someof the funds are loans that need to be repaid by recipientcountries rather than grants.59

n Regional (supra-national) initiativesArrangements for climate change action have also beenemerging at the regional level. One example is the Asia-Pacific Partnership on Clean Development and Climate.Launched in 2006, this is a partnership between seven majorAsia-Pacific countries (Australia, Canada, China, India, Japan,the Republic of Korea and the US), all of which are amongthe world’s top GHG-emitting countries. These countries arecooperating to respond to the challenge of increaseddemand for energy and the related problems of air pollution,energy security and climate change.60 The partnership

differs from the UNFCCC and the Kyoto Protocol in its focuson voluntary approaches and technological cooperation,rather than on binding emissions targets.

Another example, the European Emissions TradingScheme, became operational in 2005 and is the largestmultinational GHG emissions trading scheme in the world,involving 25 countries. It is designed to assist countries tomeet their emission reduction commitments under theKyoto Protocol. The scheme limits the amount of CO2 thatcan be emitted from large industrial facilities, such as powerplants and carbon-intensive factories. It covers almost half(46 per cent) of the EU’s CO2 emissions. Countries areallowed to trade amongst themselves and in validated creditsfrom developing countries through the CDM of the KyotoProtocol.61 The first phase of the scheme ran from 2005 to2007, and the second runs from 2008 to 2012. Because allEU member states have ratified the Kyoto Protocol, thesecond phase of the scheme was designed to support theKyoto mechanisms and compliance period. The scheme isexpected to account for around two-thirds of the overallemissions reductions which the EU plans to achieve by2020.62 However, there has been some concern that theentirety of the emissions reductions required in the secondphase could be met through various activities outside of theEU itself instead of through domestic reductions.63

National level

The sustained attention of policy-makers, scholars and themedia to climate policies at the international level has ledthem to focus less on other levels of intervention, such asthe national level.64 National governments have the primaryresponsibility for signing international agreements, curbingGHG emissions and responding to climate-related disasters.So far, their actions have focused mainly on mitigationefforts in a few energy-intensive sectors (e.g. energy, trans-portation and the built environment); but adaptation actionshave recently gained growing attention.

Some countries such as the US and China have beenrelatively less supportive of international climate policies,but have established rather robust national climate changeinitiatives. Other countries such as the UK and Germanyhave been key promoters of climate policies and have intro-duced an array of policies to achieve long-term reductions.For instance, Germany has an integrated set of ‘ecotaxes’ tofoster alternative energy development and to discouragefossil fuel consumption. The UK has designed a mixed set ofregulatory and taxation mechanisms (e.g. a levy on carbon-based electricity generation) that supports energy-efficientand renewable energy programmes.

Yet, even climate champions such as the UK andGermany face challenges complying with their carbon reduc-tion targets. For instance, by 2004 it was clear that the UK’sClimate Change Programme, introduced in 2000 to meet thecountry’s Kyoto target, would not achieve its mitigationtargets because GHG emissions had been growing at 2 percent annually from 2002.65 A review of the programme wasthus launched and a revised programme introduced in 2006.Furthermore, national mitigation strategies as well as adapta-

A number of bilat-eral initiatives toaddress climatechange haveemerged …although less attention has beengiven to financialflows emanatingfrom theseinitiatives

Even climatechampions such asthe UK andGermany facechallenges complying with theircarbon reductiontargets


tion and disaster management plans often omit urban areas66

and lack an in-depth understanding of the relevant socialscience necessary to achieve an integrated assessment of thelinkages between climate change and development,67 and toundertake that assessment in such a way that stakeholdersparticipate effectively and meaningfully.

Developing countries still lag behind developedcountries in terms of climate change action, although anincreasing number are introducing national programmes ofaction on climate change. For instance, in 2008, India intro-duced its first National Action Plan on Climate Changeoutlining a number of core missions running through to2017.68 According to the plan, the country aims to dramati-cally increase the use of solar energy and enhance energyefficiency, including within the context of urban areas. In this respect, the plan aims to make ‘habitat sustainablethrough improvements in energy efficiency in buildings,management of solid waste and modal shift to public transport’.69 Mexico’s Climate Change Programme aspires toachieve 50 per cent reductions in greenhouse gas emissionsby 2050, while also seeking to reduce the vulnerability ofhuman and natural systems to the effects of climate changeduring this period.70 China’s National Climate Change Prog-ramme states that ‘China will achieve the target of about 20per cent reduction of energy consumption per unit GDP by 2010, and consequently reduce CO2 emissions’.71 It alsooutlines a number of actions and targets to enhance adaptation to climate change, including through protectingecosystem resources such as grasslands, forests and waterreserves.72

Generally, there has been greater focus on mitigationthan adaptation responses in developing countries, althoughthe latter will be strengthened vis-à-vis the NationalAdaptation Programmes of Action (see Box 2.2). Further-more, while developing programmes of action clearlydemonstrate ‘intent’ to take action on the part of developingcountries, numerous constraints may hinder the achieve-ment of mitigation and adaptation targets, as elaboratedupon in Chapters 5 and 6 of this Global Report.

State/provincial level

National governments are not able to meet their interna-tional commitments for addressing mitigation and adaptationwithout localized action. This is not only because GHGemissions originate in activities and processes taking place atthe sub-national level (e.g. states/provinces, municipalitiesand urban centres), but also because many impacts ofclimate change are locally felt. Already, sub-national govern-ments at the state/provincial level are playing an increasinglyimportant role in climate change mitigation and adaptation.For instance, local authorities in the Federal District ofMexico City have developed important efforts to curb itsGHG emissions. One of these is the Mexico City govern-ment, which has prepared the Mexico City Climate ActionProgramme for the period of 2008 to 2012. The programmeaims to reduce greenhouse gas emissions, as well as vulnera-bility to the impacts of climate change, while strengtheningadaptation.73 Policy networks, political leaders and research

groups have been critical in launching a climate agenda.Nevertheless, this has not been enough to push effectivepolicies. Policy-making has been constrained by two sets ofinstitutional factors: the problem of fragmentation in localgovernance and lack of institutional capacity.74

The US offers an example of the multiple interactionsbetween state/province and national tiers of government.75

In the absence of federal leadership, state (and local) govern-ment efforts have become a form of ‘bottom-up governance’on climate change issues in the US. With its Global WarmingSolutions Act of 2006, California was the first state in theUS to introduce enforceable legislation to curb GHGemissions (see also Box 5.18). As per this bill, state-wideemissions are to be reduced to 1990 levels by the year2020.76 The State of Washington introduced a similar bill in2008, and even went further to identify emissions limits upto 2050.77

A number of other initiatives across different USstates have also emerged. For instance, the RegionalGreenhouse Gas Initiative is a market-based initiative involv-ing ten north-eastern and mid-Atlantic states to cap GHGemissions from the power sectors by 10 per cent by 2018.78

Another similar initiative is the US Mayors ClimateProtection Agreement, which has been signed by hundredsof mayors across the country. The agreement encouragesmayors to work towards achieving the Kyoto Protocol targetsthrough local action and to urge their state and the federalgovernment to introduce policies for GHG emissions reduc-tions.79 The Urban Leaders Adaptation Initiative, whosepartners represent nine US counties and cities (and the cityof Toronto in Canada), aims to assess and project climatechange impacts and support its partners in mitigation andadaptation activities.80 The initiative is aimed at serving as aresource for local governments and as a means to empowerlocal communities to develop and implement climate-resilient strategies.

Local/city level

Although the Kyoto Protocol does not explicitly identify arole for cities and local governments in responding toclimate change, city-level actors are actively participating inclimate strategies, projects and programmes. These includelocal authorities, community-based organizations, the privatesector, the academic sector and individuals. Local govern-ments, for instance, have held municipal leadership summitsparallel to the four COPs of 1993, 1995, 1997 and 2005.Since 2005, the ‘local government and municipal authoritiesconstituency’ has operated as an observer in the UNFCCCnegotiations.81 Indeed, ‘compared to national politicians,city leaders seem willing and able to take action to protecttheir cities against these threats and to help make a globaldifference’.82

Depending on their national contexts and histories,city authorities can have a considerable level of influenceover both GHG emissions and adaptation to climate change,as elaborated upon in detail in Chapters 5 and 6 of thisGlobal Report. In addition, they are increasingly becominginvolved in international city networks, which represent a

Developingcountries still lagbehind developedcountries in terms ofclimate changeaction

Nationalgovernments are notable to meet theirinternationalcommitments foraddressing mitigation andadaptation withoutlocalized action


City authorities canhave a considerablelevel of influenceover both GHGemissions andadaptation toclimate change

form of multilevel environmental governance across nationalboundaries with the involvement of multiple governmental,private-sector, non-profit and other civil society stakeholders.International city networks – associations between cities atthe international level – have been found to be important indeveloping the capacity of municipalities because ‘they facili-tate the exchange of information and experiences, provideaccess to expertise and external funding, and can providepolitical kudos to individuals and administrations seeking topromote climate action internally’.83 In São Paulo, Brazil, forinstance, participation in international municipal networkswas seen as import for two key reasons. First, they providedthe opportunity to ‘join the international task force againstclimate change … bypassing the nation-state with its lack ofboth binding international obligations and lack of national

limits upon GHG emission’.84 Second, such networks werean important source of personal motivation, offering individ-uals opportunities to engage with broader debates andkeeping them ‘passionate about the topic’.85

The number of these networks has been on the riseduring recent years, as illustrated in Box 2.7. A number ofthe city networks for climate change have global member-ship, while others such as the Climate Alliance and the AsianCities Climate Change Resilience Network have membershipwhich is restricted to certain world regions. While some ofthe networks have been functional since the early 1990s,others have been launched only recently. In general terms,most city networks focus on climate change mitigation,although adaptation has been receiving greater attentionduring recent years.


Box 2.7 Major international city networks and initiatives on climate change

Sources: a ICLEI, undated; b C40 Cities, undated; c Rosenzweig et al, 2010; a Clinton Foundation, undated; d World Mayors Council on Climate Change, undated; e Prasad et al, 2009; f United Cities and Local Governments,undated; g Climate Alliance, undated; h Rockefeller Foundation, 2010; i EU, undated; j Energy Cities, undated

ICLEI (Local Governments for Sustainability) waspreviously known as the International Council forLocal Environmental Initiatives. Created in 1991, it isan association of more than 1200 local governmentsfrom 70 countries who are committed to sustainabledevelopment. ICLEI has worked with cities world-wide on climate change through its urban CO2Reduction Campaign, Green Fleets Campaign and itsCities for Climate Protection Campaign (CCPCampaign). Local governments participating in theCCP Campaign commit to undertake and completefive performance milestones, as detailed in Box 5.1.a

The Large Cities Climate Leadership Group,also known as the C40 (and originally as the C20),was created in 2005 with the main goals of fosteringaction and cooperation on reducing GHG emissions,creating policies and alliances to accelerate theuptake of climate-friendly technologies. C40 iscomposed of cities from all world regions.b

The Clinton Climate Initiative was launched in2005 by the William J. Clinton Foundation to createand advance solutions to the core issues drivingclimate change. In collaboration with governmentsand businesses around the world, the initiativefocuses on three strategic programme areas: increas-ing energy efficiency in cities; catalysing thelarge-scale supply of clean energy; and working tostop deforestation. In 2006, the initiative became thedelivery partner of the C40 to assist in the deliveryof urban mitigation projects. The initiative launchedthe Climate Positive Development Program in 2009to support ‘climate positive’ development in 17urban locations across six continents. Nearly 1million people are expected to live and work inthese developments when they are complete.c

Founded in December 2005, the WorldMayors Council for Climate Change has more than 50members from all of the world and seeks to

promote policies addressing climate change and itslocal impacts; to foster the international cooperationof municipal leaders on achieving relevant climate,biodiversity and Millennium Development Goals(MDGs); and to have a say in the design of effectivemultilateral mechanisms for global climate protec-tion.d

United Cities and Local Governments (UCLG)represents and defends the interests of local govern-ments globally. In 2009, more than 1000 cities in 95countries were direct members of UCLG.e It isinvolved in the Partnership for Urban RiskReduction, an ad hoc coalition of internationalorganizations with the following objectives:

• promote worldwide awareness campaignsabout risk reduction in regions regularlyaffected by natural disasters;

• build capacity at the local level to foresee andmanage risks through the transfer of technicalknow-how to local actors and decision-makers;and

• set up a global platform for local authorities ondisaster risk reduction.f

The Climate Alliance is an association of cities andmunicipalities in 17 European countries that havedeveloped partnerships with indigenous rainforestcommunities. Since 1990, when it was founded,around 1500 cities, municipalities and districtstogether with more than 50 provinces have joinedthe alliance. NGOs and other organizations havealso joined as associate members. Its aim is topreserve the global climate through a twofoldmechanism: the reduction of GHG emissions bydeveloped countries and the conservation of forestsin developing countries. The hope is that the formerwill be achieved through an exchange of information

on best practices and by providingrecommendations, aids and tools for local climatechange policies; while the latter will be achievedthrough the organization of campaigns and politicalinitiatives on the conservation of the tropicalrainforests and the defence of indigenous rights, andby raising awareness of the political situation andliving conditions of the indigenous peoples inAmazonia.g

The Asian Cities Climate Change ResilienceNetwork is an initiative of the Rockefeller Foundationin partnership with other entities such as academic,non-governmental, governmental, international,regional and national organizations.h The networkseeks to catalyse attention, funding and action onbuilding climate change resilience for poor andvulnerable people in Asian cities. In order to accom-plish this, the network is in the process of testingand demonstrating a range of actions to buildclimate change resilience in India, Viet Nam, Thailandand Indonesia. Lessons from these interventions willbe used to support climate change resilience-building in other urban areas of the region.

The Covenant of Mayors is a mechanismintended to encourage mayors of cities in EUcountries to significantly reduce their GHGs.Accordingly, signatories to the covenant enter aformal commitment to go beyond the target to curbtheir CO2 emissions by at least 20 per cent by 2020,as already set by the EU’s Climate Action and EnergyPackage. About 2000 cities in 42 countries weresignatories to the covenant by end of 2010. Withinone year of signing the covenant, cities are expectedto prepare a Sustainable Energy Action Plan indicat-ing how they intend to meet their commitments.i

Energy Cities, the European association of morethan 1000 cities and towns, created in 1990, plays aleading role in the implementation of the covenant.j

National city networks have also been important indeveloping municipal capacity in countries where nationalgovernments have not taken action to address climatechange – for example, the Partners for Climate Protectionprogramme in Canada, ICLEI’s CCP Australia programmeand the US Mayors Climate Protection Agreement. Suchnetworks have offered political support, additional funding(paradoxically often derived from national government) and ameans of sharing information. In the case of the US MayorsClimate Protection Agreement, ‘city representatives oftencited a moral imperative to help other cities by sharing infor-mation on how best to address climate change … of citysolidarity’, while ‘friendly competition to be the greenestcity also served to further amplify engagement … engage-ment to address climate change … spread as cities promotedthemselves (and were promoted by policy actors), competedwith each other, and inspired other cities to go green’.86

However, networks have had an uneven impact, withevidence suggesting that they are more important in devel-oping the capacity of those municipalities that are alreadyleading responses to climate change, and that while thepolitical support and knowledge transfer functions that suchnetworks perform is valuable, ‘in the absence of the financialand technological resources to execute programmes, thepower of knowledge can be limited’.87 In effect, networksappear to be most important for those with a degree of exist-ing capacity to act, leading to a virtuous circle whereadditional resources and support can be accessed. However,for those without the capacity to access such networks inthe first place, such initiatives may do little to build capacityto respond to climate change and, in effect, may serve toconcentrate resources and attention on cities that arealready leading the response to mitigating climate change.

In addition to city authorities, individuals, householdsand community-based organizations and other local actorshave an important role to play in both international climatechange negotiations and city-level mitigation and adaptationactivities. These actors are recognized non-governmentalconstituencies in the UNFCCC negotiations and processes(see Box 2.8). As key emitters, the behaviour of these actorsmay directly result in the success or failure of mitigationefforts. Their actions may also be helpful in facilitating copingresponses and in the integration of climate-risk reduction, inemergency responses to climate hazards and in developmentplanning. Any efforts that local actors make to support mitiga-tion, adaptation or emergency preparedness, however, firstneeds to be made possible by the existence of infrastructuralsupport and regulative incentives. For instance, as illustratedby Dhaka, Bangladesh, and Lagos, Nigeria (see Boxes 6.1 and6.2), if not supported by broader (governmental) policies andinvestments, the responses of local actors can merely reducerather than prevent impacts. Manizales, Colombia, and Ilo,Peru, provide examples of how community-level actors canimplement effective responses.88 In these cities, community-based organizations have worked together with localauthorities and the academic sector to become vehicles formore inclusive urban governance, and have implementedactions to prevent the spread of low-income populations indangerous sites. Although these actions were not directly

aimed at addressing climate change risks, such pro-poor andpro-development policies can enhance adaptive capacity andresilience to climate hazards.

Although they are a necessary component of success-ful climate change actions, grassroots actors should not beidealized. In some cases, their extensive involvement inthese efforts can make things more difficult.89 Sometimes,for instance, local associations are closely related to thestate, or hold private or sectarian interests that distort localaction. Bringing about change through grassroots efforts isperhaps most problematic in settlements within countriesthat have experienced strong centralized control. Asdocumented in projects aimed at enhancing local capacity torespond to floods and other hazards in Guyana and VietNam,90 the attempt by the international community tomodify urban governance through funding community-sponsored development projects runs the danger that localelites or state agents will hijack the benefits of grassrootsfunding.

NGOs are also actively seeking to engage with climatechange issues, as exemplified by the Climate ActionNetwork, a network of around 500 NGOs working topromote climate change mitigation.91 However, while NGOsare plentiful in large cities, they tend to be less common oreven absent from smaller urban settlements. Where present,local NGOs are well placed to produce, accumulate andtransfer climate change knowledge. As partners in develop-

Networks … aremore important indeveloping thecapacity of thosemunicipalities thatare already leadingresponses to climatechange


Box 2.8 Non-governmental constituencies of the UNFCCC

Non-governmental organizations admitted as observers to the sessions of the United NationsFramework Convention on Climate Change (UNFCCC) have been grouped as follows:

• business and industry non-governmental organizations (BINGOs);• environmental non-governmental organizations (ENGOs);• farmers and agricultural non-governmental organizations;*

• indigenous peoples organizations (IPOs);• local government and municipal authorities (LGMA);• research and independent non-governmental organizations (RINGOs);• trade union non-governmental organizations (TUNGOs);• women and gender non-governmental organizations;*

• youth non-governmental organizations (YOUNGOs).*

A focal point is appointed for each constituency to:

• provide a conduit for the exchange of official information between their constituents andthe UNFCCC secretariat;

• assist the UNFCCC secretariat in ensuring an effective participation appropriate to anintergovernmental meeting;

• coordinate observer interaction at sessions, including convening constituency meetings,organizing meetings with officials, providing names for the speakers list and representationat official functions;

• provide logistical support to their constituents during UNFCCC sessions; and• assist the UNFCCC secretariat in realizing representative observer participation at

workshops and other limited-access meetings.Note: * Recognized on a provisional basis pending final decision on their status by COP-17 (28 November–9 December2011).

Sources: UNFCCC, undated o, undated p

ment projects aimed at reducing emissions, capturing carbonand reducing risk, they are cost effective, increase trans-parency and accountability to beneficiaries, and strengtheninclusive governance. However, by increasing their accounta-bility to upper levels of governance, NGOs can lose theirflexibility and power to contest the decisions of govern-ments and powerful interests. This can distance them fromgrassroots partners, reduce inclusiveness and horizontalaccountability, and, thus, undermine climate change mitiga-tion and adaptation efforts. On the other hand, when theycan maintain independence, NGOs can enhance climatechange policy efforts by providing a channel for feedbackbetween the grassroots level and urban government or inter-national civil society actors.92

In addition to the leading role of the IPCC in consoli-dating scientific knowledge to inform policy making,researchers around the world have been generating anddisseminating climate change information including specifi-cally in relation to cities. A case in point is the Urban ClimateChange Research Network (UCCRN), an international groupof researchers with 200 members from 60 cities globally.93

UCCRN aims to provide climate change information and dataspecifically for urban decision makers and published its firstassessment report on climate change and cities in 2011.94

The Urbanization and Global Environmental Change projectof the International Human Dimensions Programme, estab-lished in 2005, is another initiative researching theinteractions between environmental change and urbanprocesses.95

The private sector also has an important role to play inefforts aimed at curbing GHG emissions – for example,through producing more efficient vehicles and utilities,creating technologies for alternative energy, and construct-ing controlled wastewater treatment plants.96 A growingnumber of private-sector companies are also consideringhow to mitigate emissions through transforming their ownwork practices. For instance, the Carbon Disclosure Project,established in 2000, has been reporting on GHG emissionsfrom some of the world’s largest companies. In 2010, thisproject collected data from 4700 of the world’s largestcorporations, on their GHG emissions, the risks and opportu-nities related to climate change they faced, and strategies for managing them. This process was supported by 534investors with assets worth US$64 trillion.97

With regard to adaptation to climate change, theprivate sector has been subject to comparatively little atten-tion, although it is playing a key role in defining investmentsin climate-proofing infrastructures, energy utilities and otherurban sectors. Some specialized investment entities arealready taking positions around climate-related risks viainvestments in reinsurance companies, in resource pricessuch as oil and gas with the potential to be affected by hurri-canes, and through participation in alternative risk-transferproducts (e.g. insurance-linked securities such as ‘catastro-phe bonds’ and ‘weather derivatives’).98 A key concern isthat privatized actions in the area of adaptation may presenta potential conflict of interest with the public good. The roleof private security firms and privatized healthcare duringemergency periods, for instance, requires greater study, with

potentially profound implications for governance in urbanrisk management and disaster response. Nevertheless, asrecently emphasized by the executive director of theUNFCCC:

Traditional thinking would have us believe thatadaptation is the exclusive ambit of the publicsector. This is false on two levels: (1) businessneeds to adapt itself, and (2) adaptation holdsinvestment opportunities for the privatesector.99

Indeed, urban capacity to address climate change is increas-ingly shaped by the presence of more formalizedcollaboration between public and private actors.Partnerships between public, private, civil society and otheractors are becoming critical in building urban capacity torespond to climate change. For instance, in November 2010,R20 – Regions of Climate Action, an innovative coalition waslaunched to support clean technologies, climate resilientprojects, green investment and also influence national andinternational policies. The coalition includes sub-nationalgovernment members from developed and developingcountries as well as organizations and individuals from theprivate sector, academia, national governments, interna-tional organizations and civil society.100

THE POTENTIAL OF THEINTERNATIONAL CLIMATECHANGE FRAMEWORK FORLOCAL ACTIONThis section briefly reviews the opportunities and challengesposed by the existing international governance frameworkfor local action. It also discusses the existing mechanismsthat urban areas could potentially take advantage of, whatconstraints exist to the use of these mechanisms by urbanactors, and explains, briefly, some possible ways in whichthese constraints could be addressed.

A key factor constraining urban actors’ use of mecha-nisms within the international climate change framework isthe fact that these mechanisms are primarily addressed tonational governments and do not indicate a clear process bywhich urban areas and actors may participate. The relatedinternational structure for climate change financing, inparticular, has been described as ‘diverse and complex, andnot primarily designed for local governments’.101 Thefunding mechanisms of the UNFCCC discussed earlier inthis chapter (see Box 2.2) can be used to finance projectswithin urban areas, but they are only accessible for urbanactors through their national governments. Even thoughnational governments represent the interests of their urbanpopulations in international discussions on allocating respon-sibility for climate change mitigation, and in developinginternational funding mechanisms and institutions tosupport adaptation, getting urban priorities moved up onnational agendas can be problematic, at best. For instance,

Partnershipsbetween public,private, civil societyand other actors arebecoming critical inbuilding urbancapacity to respondto climate change

Mechanisms withinthe internationalclimate changeframework … do notindicate a clearprocess by whichurban areas andactors may participate


although National Adaptation Programmes of Action havebeen prepared for developing countries under the LeastDeveloped Countries Fund, there have been few initiativesfor adaptation at the sub-national level.102

Similarly, emissions trading currently takes placebetween countries and groups of countries or tends to targetparticular industries, thereby offering limited possibilities foractions at the urban level. For instance, the EuropeanEmissions Trading Scheme targets carbon-intensive factoriesand power plants by capping the amount of CO2 that theyemit. While some of these facilities are certainly locatedwithin urban areas, and it may be safe to assume that a largepercentage of their output serves urban needs, local authori-ties are not generally in direct control of these activities. Ofcourse, some exceptions exist, where, for instance, an urbancentre owns a public utility, such as one for electricity gener-ation.

In contrast, CDM offers significant potential for urbanprojects in developing countries in such sectors as transporta-tion, waste and the building industry. Indeed, a recent studyshows that it is one of the international financing mecha-nisms that city authorities are most aware of. However, urbanCDM-based projects account for only 8.4 per cent of the totalnumber of CDM projects registered with the UNFCCC in2009. Most of these were related to solid waste, with onlytwo projects related to transport. Furthermore, the majorityof the urban CDM projects are concentrated in a fewcountries – namely, Brazil (36 per cent), China (14 per cent),Mexico (5 per cent) and India (2 per cent).103

A number of reasons have been identified for thesmall proportion of CDM projects being urban based. First,the responsibility for climate change action is perceived tolie with national rather than local governments. Second, city authorities are already overwhelmed by immediate local challenges and have difficulty justifying climate change-related projects and expenditures. Third, the financial resources required for climate change action (e.g. introducing energy-efficient technology and equipment)may be absent in developing countries. Fourth, the hightransaction costs associated with project development andapproval by authorities has been identified as an additionalconstraint.104 Additional barriers to expanding the use ofCDM in urban areas are considered in greater detail inChapter 5 (see section on ‘Financial resources’).

The joint implementation mechanism is very similarto CDM, but it applies only between developed countries.105

Since most of the joint implementation projects are incountries with economies in transition and emissions reduc-tion activities are generally more expensive in thesecountries compared to similar activities in developingcountries, the joint implementation mechanism has beenused far less than the CDM.106 The use of joint implementa-tion by urban actors has, therefore, also been very limited.

A further major challenge for local authorities to takeadvantage of the international climate change framework toimplement climate responses locally is that they are oftenoverwhelmed by competing priorities. Besides coordinatingpolicy efforts with organizations and actors at the nationaland state/provincial levels to address an array of non-climate-

related developmental and environmental issues, they nowneed to deal with a multitude of issues centring on climate-related mitigation, adaptation, development, and disasterpreparedness and response. While coping with a myriad ofcompeting priorities within their boundaries, they also needto explore ways in which they can better connect to multiplelevels of action and information on climate change, andknow how their issues fit into the larger picture of regional,national and international climate change issues. In addition,mismatches exist between climate and local policy-makingtimeframes. Given the fact that many of the cause-and-effectrelationships are long term and potentially irreversible, theyrequire planning that goes beyond the tenure, the adminis-trative power and even the lifetime of most currentdecision-makers and other stakeholders.

Despite the above challenges, local authorities cancoordinate efforts with national and state/provincial authori-ties to make use of financial resources offered under theUNFCCC to invest in local mitigation initiatives which offerhigh mitigation potentials. These include investments in theareas of transport, energy generation, waste managementand the like. Local urban authorities and actors can also takeadvantage of existing networks and organizations that focusspecifically on enhancing local climate change action at thecity level. Urban authorities could get support from theUNFCCC to finance adaptation projects, not only throughtheir national governments, but also through their participa-tion in various city networks. For instance, the Federation ofCanadian municipalities is working with ICLEI through theirCities for Climate Protection Campaign (see Box 2.7). A totalof 180 Canadian municipalities are engaged in assessing andreducing GHG emissions through the campaign.107 Severalinitiatives also offer opportunities for urban authorities tolearn from and share climate change best practices andlessons (see Box 2.7).

Urban authorities may also try to benefit from initia-tives of multilateral and bilateral organizations seeking toenhance the capacity of developing countries to take part inand take advantage of international climate change discus-sions and the resulting instruments and mechanisms (seeBox 2.7). For instance, The World Bank’s Carbon FinanceAssist Programme seeks to enhance the capacity of develop-ing countries to engage with the flexible mechanisms of theKyoto Protocol.108 Similarly, the Climate Alliance aims toenhance the participation of developing countries in CDMs.UNEP’s Campaign on Cities and Climate Change explicitlyseek to support the engagement of cities in internationalclimate change negotiations and forums.

Local authorities can also seek to harmonize climatechange interventions with existing development interven-tions and concerns. For instance, mitigation can beintegrated within local development concerns such asenergy security and infrastructure provision. Adaptationmeasures can serve and be integrated not only within disas-ter risk reduction, but also within components of thedevelopment agenda such as land-use planning and access towater, sanitation and housing. For instance, existing copingactions such as community savings networks might becombined with insurance mechanisms sponsored by NGOs.

A further majorchallenge for localauthorities to takeadvantage of theinternationalclimate changeframework…is thatthey are oftenoverwhelmed bycompeting priorities

Urban authoritiescould get supportfrom the UNFCCCto finance adaptationprojects… throughtheir participation in various citynetworks


CONCLUDING REMARKSDuring the last few decades, climate change has gainedimportance as a major 21st-century challenge partly due tothe consolidation of scientific evidence of the contributionof human activities to global warming. Knowledge – whethergenerated by scientific communities or brokered by themedia, scientific entrepreneurs or NGOs at different levels(from the international to the local) – has been a fundamen-tal factor shaping climate action at all levels. However, themove from knowledge to action is not straightforward. Thepolitical mechanisms by which individuals, groups, organiza-tions and governments translate the scientific knowledge ofclimate change into concrete actions have played a criticalrole in this regard.

The UNFCCC and the Kyoto Protocol are the keyelements of the overarching framework adopted by worldgovernments to guide climate change responses globally.Although the adoption of the Kyoto Protocol was hailed as asignificant milestone and has enabled substantial emissionsreductions since, the failure to reach a legally binding agree-ment for the period after the end of the protocol’scommitment period in 2012 is seen as a major failure ofinternational climate change negotiations.

The UNFCCC and its Kyoto Protocol coexist with amultitude of parallel initiatives and frameworks operating atdifferent sectors and spatial levels. Even if national govern-ments are leading negotiations of climate change agreementsat the international level, mitigation and adaptation activitiesare being implemented by numerous other actors at theregional, sub-national (e.g. state/provincial) and local levels.The sustained attention of policy-makers, the scientificcommunity and the media to climate policies at the interna-tional level has mainly led them to overlook these otherequally important levels of climate intervention.

Local action is indispensable for the realization ofnational climate change commitments agreed through inter-national negotiations. Yet, the international frameworkdescribed in this chapter presents both challenges andopportunities for climate change action at the local city level.Most of the mechanisms within the international climatechange framework are addressed primarily to nationalgovernments and do not indicate a clear process by whichlocal governments, stakeholders and actors may participate.Furthermore, local authorities can quickly be overwhelmed

by competing priorities and therefore may not activelypursue opportunities offered by the international gover-nance framework. Thus, in practice, mitigation andadaptation actions have been by-products of policiesdesigned to address more pressing local problems orproblems for which there is more pressure by interestedparties. The overall complexity of the international climatechange framework – as well as the multiplicity of relatedactors and mechanisms – may further prevent city authori-ties from benefiting from available opportunities. Also,administrative structures, party politics, political timetables,individual ambitions, inertias, and many other institutionaland political constraints need to be overcome, thus requiringa broader-based institutional capacity for climate action. Itsabsence has deterred key mitigation and adaptation efforts.Yet, in some cases it has become another source of opportu-nity for state and local actors to fill a leadership gap.

Despite the challenges, the multilevel climate changeframework briefly described in this chapter does offer oppor-tunities for local action at the city level. While theproportions remain low, urban-based emissions reductionprojects are being implemented through some of the mecha-nisms of the UNFCCC (e.g. the CDM). There is also greatpotential for expanding such projects given the role of urbanareas in contributing to GHG emissions.109 In addition,today, more urban authorities than ever before participate ininternational city networks for climate change adaptationand mitigation. These urban actors have developed a moreaggressive approach, seeking to secure the economiccompetitiveness of their cities and to get a local voice ininternational negotiations and organizations.

The crux of the challenge is that actors of climatechange at all levels – including governments, NGOs and civilsociety that are, more often than not, preoccupied withimmediate and often localized interests and priorities – needto move within short timeframes to guarantee long-term andwide-ranging global interests, which can seem remote andunpredictable at best. The hope is that a wave of actionsfrom local actors centring their work at the local level, whereall the impacts of climate change will ultimately be felt, willjoin together to create the momentum to build broad-basedsupport for mitigation and increase adaptive capacity in theareas and populations that are most vulnerable to the effectsof climate change.

Local action is indispensable for the realization ofnational climatechangecommitmentsagreed throughinternational negotiations


1 Biermann et al, 2009, p31.2 Betsill and Bulkeley, 2007;

Alber and Kern, 2008;Biermann et al, 2008.

3 ICLEI, 2010.4 UNFCCC, undated a. 5 UNFCCC, undated b.6 UN, 1992, Article 3. See also

CISDL, 2002.7 De Lucia and Reibstein, 2007.8 UN, 1992.9 UNFCCC, undated c.10 UNFCCC, undated d.11 UNFCCC, undated d.12 UNFCCC, undated e.13 UNFCCC, 1995.14 UNFCCC, 1996.15 Bodansky, 2001.16 See section entitled ‘The Kyoto

Protocol’ below.17 GEF, undated.18 Bodansky, 1993, cited in Gupta

and van Asselt, 2006.19 Gupta and van Asselt, 2006,

p84.20 Biermann et al, 2008.21 UNFCCC, undated r.22 UNFCCC, undated k.23 See previous section on ‘The

United Nations FrameworkConvention on ClimateChange’; UNFCCC, undated e.

24 UNFCCC, undated l.25 UN, 1998.26 After Australia’s ratification of

the protocol in 2007, the US isthe only developed countrynot to have ratified the KyotoProtocol.

27 UN, 1998.

28 Bulkeley and Betsill, 2003.29 Gilbertson and Reyes, 2009. 30 Disch, 2010, p55.31 Richman, 2003. 32 UNFCCC, 2010.33 Beccherle and Tirole, 2010.34 Bodansky, 2001; Aldy et al,

2003.35 Biermann et al, 2008.36 Held and Hervey, 2009. 37 UN, 2008.38 UNEP, undated a.39 UNEP, undated b.40 WMO, 2007.41 UN-REDD, undated.42 UNEP et al, 2010.43 UNISDR, undated a. 44 UNISDR, undated b.45 Sohn et al, 2005.46 World Bank, undated a.47 World Bank, 2009a.48 CFCB, undated.49 World Bank, 2010d.50 ADB, undated.51 Inter-American Development

Bank, 2007.52 European Investment Bank,

2010.53 For example, see OECD, 2010.54 OECD, 2009.55 Atteridge et al, 2009.56 GCCA, undated a.57 European Commission, 2009;

GCCA, undated b.58 GCCA, undated c.59 Bird and Peskett, 2008.60 Asia-Pacific Partnership on

Clean Development andClimate, undated.

61 Parker, 2006. See also Box 2.2.

62 European Commission, 2009.63 Gilbertson and Reyes, 2009,

p42.64 Rabe, 2007.65 Department of Energy and

Climate Change, undated.66 Bulkeley and Betsill, 2003;

Pelling, 2005; Satterthwaite etal, 2007a.

67 Satterthwaite et al, 2007a;Romero Lankao, 2007b; Moser,2010.

68 Pew Center on Global ClimateChange, 2008.

69 Pew Center on Global ClimateChange, 2008.

70 Sandoval, 2009.71 People’s Republic of China,

2007.72 People’s Republic of China,

2007.73 Secretaría del Medio Ambiente

del Distrito Federal, 2008.74 Romero Lankao, 2007b.75 Rabe, 2007; Wheeler, 2008; see

also Pew Center on GlobalClimate Change, undated.

76 California Solutions for GlobalWarming, undated.

77 Department of Ecology, Stateof Washington, undated.

78 Regional Greenhouse GasInitiative, undated.

79 The United States Conferenceof Mayors, 2008.

80 Centre for Clean Air Policy,undated.

81 ICLEI, 2010, p15. See Box 2.8.82 Rosenzweig et al, 2010.83 Bulkeley et al, 2009, p26; see

also Collier, 1997; Bulkeley andBetsill, 2003; Bulkeley andKern, 2006; Granberg andElander, 2007; Holgate, 2007;Kern and Bulkeley, 2009.

84 Setzer, 2009, p1085 Setzer, 2009, p10.86 Warden, 2009, p8.87 Gore et al, 2009, p22.88 See the section on ‘Adaptation

planning and local governance’in Chapter 6.

89 Pelling, 2005.90 Pelling, 1998.91 CAN, undated.92 Pelling, 2005.93 Rosenweig et al, 2010.94 Rosenweig et al, 2011.95 Rosenweig et al, 2010; IHDP,

undated.96 IPCC, 2007a.97 PricewaterhouseCoopers,

2010. 98 Wilbanks et al, 2007.99 Figueres, 2010.100 Office of the Governor,

California, US, undated.101 ICLEI, 2010, p79.102 ICLEI, 2010.103 ICLEI, 2010.104 World Bank, 2010a; Clapp et al,

2010. 105 See Box 2.3.106 Gilbertson and Reyes, 2009.107 Federation of Canadian

Municipalities, 2009.108 See the section on ‘Other

multilateral organizations’above.

109 See Chapter 3.


NOTES

The allocation of responsibility for greenhouse gas (GHG)emissions – and, hence, climate change – is an importantglobal policy debate. Indeed, the importance of responsibil-ity is explicitly recognized in the United Nations FrameworkConvention on Climate Change (UNFCCC) allocation of‘common but differentiated responsibilities’ amongcountries for addressing emissions.1 As shown in Chapter 1,urban areas – which are now home to more than half of theworld’s population – clearly have an important role to play infacilitating reduced emissions; yet the contribution of urbanareas to emissions is often unclear.

There are several reasons why it is important toconsider the contribution of urban areas to climate change.First, a range of activities are associated with cities and theirfunctioning that contribute to GHG emissions. Transport-ation, energy generation and industrial production withinthe territorial boundaries of towns and cities generate GHGemissions directly. Urban centres rely on inward flows offood, water and consumer goods that may result in GHGemissions from areas outside the city. In addition, individualsconsume a range of goods and services that may have beenproduced locally or outside the urban area. An analysis of therelative impacts of these activities is an important steptowards understanding the extent of the contribution ofurban areas to climate change.

Second, measuring emissions from different citiesprovides a basis for comparisons to be made and the potentialfor inter-urban competition and cooperation. Climate-friendlydevelopment has the potential to attract external investment,and the growing importance of international urban networks2

provides spaces for learning and knowledge sharing.Emissions measuring has recently been inserted into globalpolicy debates. For example, the United Nations EnvironmentProgramme (UNEP), the United Nations Human SettlementsProgramme (UN-Habitat) and the World Bank launched anInternational Standard for Determining Greenhouse GasEmissions for Cities at the World Urban Forum in Rio deJaneiro in March 2010.3 This standard provides a commonmethod for cities to calculate the amount of GHG emissionsproduced within their boundaries.

Third, an assessment of the contribution of cities toclimate change is a vital first step in identifying potentialsolutions. The large and growing proportion of the Earth’s

population living in towns and cities, and the concentrationof economic and industrial activities in these areas, meansthat they need to be at the forefront of mitigation. The estab-lishment of emission baselines is necessary if effectivemitigation benefits are to be identified and applied.

Finally, it is important to highlight the differencesbetween production- and consumption-based analyses ofGHG emissions. Most assessments of the contribution ofcities – and countries – to climate change have focused onthe emissions that are produced by activities taking placewithin given territorial boundaries. However, an alternativeapproach is to consider the emissions associated with theconsumption patterns of individuals, recognizing that manyagricultural and manufacturing activities that meet the needsof urban residents take place outside city boundaries, andoften in other countries. This consumption-based approachprovides an alternative framework for suggesting appropriateways of reducing GHG emissions by focusing on consumerchoices as potential drivers for mitigation.

The first two sections of this chapter explain thescientific and technical basis for measuring GHG emissionsfrom urban areas. The third section presents findings from awide range of urban emissions inventories to show howthese vary from place to place, while the fourth sectiondescribes the factors influencing emissions at the urbanlevel. Finally, the chapter examines different approaches tomeasuring GHG emissions and shows that the simple analy-ses that have been frequently used until now are no longersufficient for addressing this urgent global challenge.

MEASURING GREENHOUSEGAS EMISSIONSIn order to account for the contribution of urban areas toclimate change, it is necessary to measure their emissions ofGHGs.4 This requires particular methodologies to accountfor the various activities and the volume of these gases thatthey produce. And in order to make meaningful comparisonsover time, or between different places, there is a need forstandardized protocols to be developed. According to theUNFCCC, inventories should meet the following five qualitycriteria:5

The allocation ofresponsibility forgreenhouse gas …emissions – and,hence, climatechange – is animportant globalpolicy debate

Climate-friendlydevelopment has thepotential to attractexternal investment

the … InternationalStandard forDeterminingGreenhouse GasEmissions for Cities… provides acommon method for cities to calculatethe amount of GHGemissions producedwithin their boundaries

C H A P T E R

THE CONTRIBUTION OF URBANAREAS TO CLIMATE CHANGE

3

1 Transparency: assumptions and methodologies shouldbe clearly explained.

2 Consistency: the same methodology should be used forbase and subsequent years.

3 Comparability: inventories should be comparablebetween different places.

4 Completeness: inventories should cover all relevantsources of emissions.

5 Accuracy: inventories should be neither over nor undertrue emissions.

International protocols for measuring greenhouse gas emissions

As noted in Chapter 2, the UNFCCC is the global instrumentresponsible for ensuring that countries measure nationalGHG emissions and set targets for their reduction. Underthe Convention, national governments gather and shareinformation on GHG emissions; launch national strategies toreduce emissions; and cooperate to prepare for adaptation toclimate change impacts. A total of 36 developed countrieshave – under the Kyoto Protocol – accepted emission ‘caps’that limit their total GHG emissions within a designatedtimeframe and are required to submit annual inventories oftheir national emissions, while other signatories to the KyotoProtocol submit emission inventories in their periodicnational communications.

National inventories are prepared according to adetailed set of criteria developed by the IntergovernmentalPanel on Climate Change (IPCC): the IPCC Guidelines forNational Greenhouse Gas Inventories.6 This is a detailedseries of five volumes prepared by the IPCC as a result of arequest by the UNFCCC. It is intended to ensure that

countries are able to fulfil their commitments under theKyoto Protocol and subsequent international agreements.These criteria recognize that figures will be estimates, butseek to ensure that these do not contain any biases thatcould have been identified and eliminated. There are alsodifferent tiers of estimation methods, which take intoaccount varying availability of data between countries. Theinventories provide measuring strategies and global warmingpotentials for the full range of GHGs, and include method-ologies for estimating emissions in four key sectors. Theseare: energy; industrial processes and product use; agricul-ture, forestry and other land use; and waste (see Table 3.1).

In the case of urban areas, emissions from the use offossil fuels, industrial processes and product use, and wasteare of particular importance. Stationary combustion mainlyrelates to energy industries, manufacturing industries andconstruction; while mobile combustion includes transporta-tion emissions from civil aviation, road transportation,railways and waterborne navigation (although only withinnational boundaries – fuel use associated with internationalmaritime transportation is not included). These distinctionsare important, as – taken as a whole – energy, transportationand buildings account for almost half of all global emissions(see Figures 1.4 and 3.1).

National GHG inventories are based on the assump-tion that a country is responsible for all emissions producedwithin its area of jurisdiction. As a pragmatic measure tofacilitate national targets and reductions, this is likely to bethe only enforceable strategy – as countries only have legisla-tive power within their own national boundaries. However, itmeans that the patterns of consumption that drive emissions(notably in the energy and industry sectors) are often veiled.For example, many polluting and carbon-intensive manufac-turing processes are no longer located in developedcountries, but have been sited elsewhere in the world totake advantage of lower labour costs and less rigorousenvironmental enforcement, and this reduces emissions indeveloped countries.7 This is an important issue whenassessing the underlying factors influencing emissions,which is discussed later in this chapter.8

Protocols for measuring corporategreenhouse gas emissions

As industries and corporations have become increasinglyaware of the impact that their activities have upon theenvironment, they have increasingly engaged in conductingGHG inventories. This enables companies to develop effec-tive strategies to manage and reduce GHG emissions, and tofacilitate their participation in voluntary and mandatoryemissions reductions programmes. The most frequentlyutilized of these is the Greenhouse Gas Protocol developedby the World Resources Institute (WRI) and the WorldBusiness Council for Sustainable Development (WBCSD).This protocol puts forward an accounting system that isbased on relevance, completeness, consistency, transparencyand accuracy, and provides a mechanism by which private-sector actors can contribute to the global goal of reducingGHG emissions.9

The UNFCCC is theglobal instrumentresponsible forensuring thatcountries measurenational GHGemissions and settargets for theirreduction


Table 3.1

Sectors assessed fornational GHG inventories

Sector Sub-sectors

Energy Stationary combustionMobile combustionFugitive emissionsCO2 transport, injection and geological storage

Industrial processes Mineral industry emissionsand product use Chemical industry emissions

Metal industry emissionsNon-energy products from fuels and solvent useElectronics industry emissionsEmissions of fluorinated substitutes for ozone-depleting substancesOther product manufacture and use

Agriculture, forestry Forest landand other land use Cropland

GrasslandWetlandsSettlementsOther landEmissions from livestock and manure managementNitrous oxide emissions from managed soils, and CO2 emissions from lime and urea applicationHarvested wood products

Waste Solid waste disposalBiological treatment of solid wasteIncineration and open burning of wasteWastewater treatment and discharge

Note: The GHGs to be assessed are CO2, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulphur hexafluo-ride, nitrogen trifluoride, trifluoromethyl sulphur pentafluoride, halogenated ethers and other halocarbons (see also Table1.3).

Source: IPCC, 2006

The protocol addresses the issues peculiar to thecorporate sector of accounting for emissions from groupcompanies, subsidiaries, affiliated companies, non-incorpo-rated joint ventures or partnerships, fixed-asset investmentsand franchises. The concept of ‘scope’ was developed in thisprocess,10 which takes into account direct and indirect GHGemissions in a more effective manner (see Table 3.2). It alsodescribes the processes by which GHG emissions can beidentified and calculated, how these can be verified for aformal reporting process, and how targets can be set.

Protocols for measuring local governmentgreenhouse gas emissions

Urban authorities often function at two distinct levels. First,they function as business enterprises – owning or leasingbuildings, operating vehicles, purchasing goods and carryingout various other activities. In this regard, urban authoritiescan assess their emissions as corporate entities, includingthe direct and indirect impacts of their work. Second, urbanauthorities function as governments – with varying levels ofoversight for and influence on the activities taking placewithin the spatial area over which they have jurisdiction.

The most widely accepted methodology for measuringemissions within local government boundaries has beendeveloped by Local Governments for Sustainability (ICLEI),which is an international association of more than 1000 localgovernment authorities that have made a commitment tosustainable development. More than 700 of these aremembers of the Cities for Climate Protection Campaign (seeBox 2.7), which aims to assist cities in adopting policies toreduce local GHG emissions, improve air quality, andimprove urban liveability and sustainability. The campaignsets five milestones for participating authorities:

1 Conduct a baseline emissions inventory and forecast.2 Adopt an emission reduction target for the forecast

year.3 Develop a local action plan.4 Implement policies and measures.5 Monitor and verify results.11

The first stage of this process requires an emissions inven-tory; yet no appropriate methodology existed when thecampaign was devised. The IPCC methodology for countriesdoes not provide specifications at the local authority level fordiscussing energy consumption, transportation or wastedisposal; and the existing corporate accounting protocols donot cover the details of municipal operations such as street

lighting, landfill emissions and emissions from wastewatertreatment or other industrial activities.

ICLEI’s International Local Government GHGEmissions Analysis Protocol12 was developed in response tothis need. This protocol takes into account both governmentand community sectors, using the main categories derivedfrom the IPCC’s guidelines on national inventories of GHGemissions from stationary combustion, mobile combustion,fugitive emissions,13 product use, other land use and waste.The protocol organizes government emissions according to:

• buildings and facilities;• electricity or district heating/cooling generation;• vehicle fleet;• street lighting and traffic signals;• water and wastewater treatment, collection and distri-

bution;• waste;• employee commute;• others.

It also breaks down the ‘macro-sectors’ used by the IPCCmethodology (shown in Table 3.1) into community sectorsfor analysis, as shown in Table 3.3. ICLEI’s frameworkprovides the basis for the calculation of most current city-wide GHG emissions inventories.14 It also recognizes theconcept of scopes15 in both government and communitysectors (see Table 3.4). However, these do not extend as faras the consumption-based approaches,16 many of which areimpractical given the financial and technical resources avail-able to local authorities to conduct inventories of this type. A more detailed consumption-based analysis requires muchmore information relating to the embedded carbon contentof consumer goods purchased by individuals.

The most widelyaccepted methodology formeasuring emissionswithin local government boundaries has been developed byLocal Governmentsfor Sustainability(ICLEI)

35The Contribution of Urban Areas to Climate Change

Table 3.2

Emissions scopes forcompanies

Table 3.3

ICLEI categorization ofcommunity sectors

Sector Definition Examples

Scope 1: Direct GHG emissions that occur from sources Emissions from combustion in owned or controlled boilers, furnaces, owned or controlled by the company. vehicles; emissions from chemical production in process equipment.

Scope 2: GHG emissions from the generation of purchased Purchased electricity in which the emissions physically occur at the electricity consumed by the company. facility where electricity is generated.

Scope 3 (optional): GHG emissions that are a consequence of the Extraction and production of purchased materials; transportation of activities of the company, but occur from sources purchased fuels; use of sold products and services.not owned or controlled by the company.

Source: WRI/WBCSD, undated

Macro-sector (IPCC) Community sector (ICLEI)

Energy Stationary combustion ResidentialCommercialIndustrial

Mobile combustion TransportationFugitive emissions Other

Industrial processes and product use OtherAgriculture, forestry and other land use Agricultural emissions

OtherWaste Solid waste disposal Waste

Biological treatment of solid wasteIncineration and open burning of wasteWastewater treatment and discharge

Source: ICLEI, 2008

New baseline inventories for urban emissions

Increased interest in the contribution of urban areas to GHGemissions, and a growing recognition of the importance ofurban areas in addressing the causes of climate change,means that there have been increasing attempts to developappropriate inventories to account for city-level emissions.Many of these now grapple with complex issues of produc-tion- and consumption-based measures for allocatingemissions.17 An important component of these inventories isthe setting of baselines, which can then be used to settargets for emissions reductions in subsequent years. It isalso possible that a widely accepted baseline methodologymight form the basis for emissions trading schemes, or forurban areas as a whole to trade carbon credits either on theformal or the voluntary market.18 Table 3.5 presents a WorldBank compilation of GHG emission baselines for selectedcities and countries.

In addition, the recently launched InternationalStandard for Determining Greenhouse Gas Emissions forCities19 provides a common method for cities to calculatethe amount of GHG emissions produced within their bound-aries. This standard builds on and is consistent with theIPCC protocols for national governments, and provides acommon format to facilitate compilation by local authorities.It is hoped that this will provide a standard that can be usedby cities around the world.

Boundary issues

Efforts to develop a standardized globally comparablemethodology for GHG emissions at the local or municipallevel are made more complicated by the wide range ofboundary definitions used for these areas. In general, thesmaller the scale, the greater the challenges posed by‘boundary problems’ in which it is increasingly difficult toidentify which emissions ought or ought not to be allocatedto a particular place.20

The importance of boundary definitions is clear fromstudies of urban populations, where differences in how

governments define city boundaries have direct effects ofspatial structure. For instance, it has been shown how eightdifferent lists of the world’s 20 largest cities vary, with onlynine cities appearing on all eight lists; and with four differ-ent areas competing for the first two ranks.21 The populationfigures for some large cities are for people living within long-established city boundaries enclosing areas of only 20 to 200square kilometres; whereas for others (particularly in China) this includes regions with many thousands of square kilometres and a significant rural population.22 Thesecomplications – related to different definitions of cities andurban areas, and different conceptions of the spatial extentof these – are all equally relevant in relation to identifyingGHG emissions from a particular urban area. Similarly,energy consumption in urban areas in the US can varybetween 37 and 81 per cent depending on how these areasare defined and bounded in space.23 Thus, even within asingle country, the potential contribution of urban areas toclimate change can vary by a factor of two depending on thespatial definition of these areas.24

THE SOURCES OFGREENHOUSE GASEMISSIONSTowns and cities do not themselves emit GHGs. Rather,specific activities that take place within urban areas – andthat are undertaken in different ways by people of differentages, genders and income groups – are the sources of theseGHGs. Different activities or sectors emit different quanti-ties of different gases – with diverse impacts upon climatechange (see Figure 3.1). Some of these activities have beenintegral to the process of urbanization over the last 300years, and some have the clear potential to reduce emissionsto mitigate climate change.

The main sources of GHG emissions from urban areasare related to the consumption of fossil fuels: whether this isfor electricity supply, transportation or industry. This sectionexplores the main sources of GHG emissions from urban

A … consumption-based analysisrequires much moreinformation relatingto the embeddedcarbon content ofconsumer goodspurchased byindividuals

Efforts to develop a… methodology forGHG emissions atthe local or municipal level aremade more complicated by thewide range ofboundarydefinitions used forthese areas

Towns and cities donot themselves emitGHGs. Rather,specific activitiesthat take placewithin urban areas… are the sources ofthese GHGs


Definitions Examples

Government operations emissions:Scope 1: Direct emission sources owned or operated by A municipal vehicle powered by gasoline or a municipal generator

the local government. powered by diesel fuel.Scope 2: Indirect emission sources limited to electricity, Purchased electricity used by the local government, which is associated

district heating, steam and cooling consumption. with the generation of GHG emissions at a power plant.Scope 3: All other indirect or embodied emissions over which the Emissions resulting from contracted waste-hauling services.

local government exerts significant control or influence.Community-scale emissions:Scope 1: All direct emissions sources located within the Use of fuels such as heavy fuel oil, natural gas or propane used for heating.

geopolitical boundary of the local government.Scope 2: Indirect emissions that result as a consequence of Purchased electricity used within the geopolitical boundaries of the

activity within the jurisdiction’s geopolitical boundary jurisdiction associated with the generation of GHGs at the power plant.limited to electricity, district heating, steam and cooling consumption.

Scope 3: All other indirect and embodied emissions that occur Methane emissions from solid waste generated within the community as a result of activity within the geopolitical boundary. which decomposes at landfills either inside or outside of the community’s

geopolitical boundary.

Source: compiled from ICLEI, 2008

Table 3.4

Emissions scopes forlocal authorities


Annual GHG emissions Annual GHG emissions (tonnes of CO2eq (tonnes of CO2eq

Country per capita) Year City per capita) Year

Argentina 7.64 2000 Buenos Aires 3.83Australia 25.75 2007 Sydney 0.88 2006Bangladesh 0.37 1994 Dhaka 0.63Belgium 12.36 2007 Brussels 7.5 2005Brazil 4.16 1994 Rio de Janeiro 2.1 1998

São Paulo 1.4 2000Canada 22.65 2007 Calgary 17.7 2003

Toronto (City of Toronto) 9.5 2004Toronto (Metropolitan Area) 11.6 2005Vancouver 4.9 2006

China 3.40 1994 Beijing 10.1 2006Shanghai 11.7 2006Tianjin 11.1 2006Chongqing 3.7 2006

Czech Republic 14.59 2007 Prague 9.4 2005Finland 14.81 2007 Helsinki 7.0 2005France 8.68 2007 Paris 5.2 2005Germany 11.62 2007 Frankfurt 13.7 2005

Hamburg 9.7 2005Stuttgart 16.0 2005

Greece 11.78 2007 Athens 10.4 2005India 1.33 1994 Ahmedabad 1.20

Delhi 1.50 2000Kolkata 1.10 2000

Italy 9.31 2007 Bologna (Province) 11.1 2005Naples (Province) 4.0 2005Turin 9.7 2005Veneto (Province) 10.0 2005

Japan 10.76 2007 Tokyo 4.89 2006Jordan 4.04 2000 Amman 3.25 2008Mexico 5.53 2002 Mexico City (City) 4.25 2007

Mexico City (Metropolitan Area) 2.84 2007Nepal 1.48 1994 Kathmandu 0.12The Netherlands 12.67 2007 Rotterdam 29.8 2005Norway 11.69 2007 Oslo 3.5 2005Portugal 7.71 2007 Porto 7.3 2005Republic of Korea 11.46 2001 Seoul 4.1 2006Singapore 7.86 1994Slovenia 10.27 2007 Ljubljana 9.5 2005South Africa 9.92 1994 Cape Town 11.6 2005Spain 9.86 2007 Barcelona 4.2 2006

Madrid 6.9 2005Sri Lanka 1.61 1995 Colombo 1.54

Kurunegala 9.63Sweden 7.15 2007 Stockholm 3.6 2005Switzerland 6.79 2007 Geneva 7.8 2005Thailand 3.76 1994 Bangkok 10.7 2005UK 10.50 2007 London (City of London) 6.2 2006

London (Greater London Area) 9.6 2003Glasgow 8.8 2004

US 23.59 2007 Austin 15.57 2005Baltimore 14.4 2007Boston 13.3Chicago 12.0 2000Dallas 15.2Denver 21.5 2005Houston 14.1Philadelphia 11.1Juneau 14.37 2007Los Angeles 13.0 2000Menlo Park 16.37 2005Miami 11.9Minneapolis 18.34 2005New York City 10.5 2005Portland, OR 12.41 2005San Diego 11.4San Francisco 10.1Seattle 13.68 2005Washington, DC 19.70 2005

Note: Sources of the data presented above and details on which emissions have been included in the baselines are specified in the original source.

Source: based on World Bank, undated c

Table 3.5

Representative GHGbaselines for selectedcities and countries

areas, with a focus on energy supply (for electricity genera-tion, transportation, commercial and residential buildings),industry, waste, agriculture, land-use change and forestry. Itexamines the activities that contribute to GHG emissionsfrom these sectors, the types of gases that are generated andthe importance of these for climate change. It also highlightsthe potential for mitigation in each of these sectors, settingthe stage for detailed discussion in Chapter 5.

Energy supply for electricity generation

Energy is perhaps the broadest possible category for assess-ing GHG emissions. The combustion of fossil fuels is themajor source of these, and is used throughout the world forelectricity generation, heating, cooling, cooking, transporta-tion and industrial production. Energy is obtained from

fossil fuels, biomass, nuclear power, hydroelectric genera-tion and other renewable sources. Urban areas rely heavilyon energy systems (shaped by the quantity of energy used),the energy structure (types of energy forms used) and thequality of the energy (its energetic and environmentalcharacteristics). This section will thus focus on the use ofenergy for electri-city generation in urban areas, the differ-ent sources of energy and the implications for GHGemissions. Overall (in 2008), transport accounted forapproximately 1.6 per cent of global electricity use; indus-try accounted for 41.7 per cent; while other sectors(agriculture, commercial and public services, residential,and non-specified other sectors) accounted for 56.7 percent.25 The particular aspects of electricity consumption byindustry, and in commercial and residential buildings, willbe examined later in this section.

Electricity functions as an ‘energy carrier’ – that is, anintermediate step between the original source of energy andthe end user. In concentrated and densely populated urbanareas, electricity is much more practical than the more directuse of fuels, particularly because large generation plants canbe located hundreds of kilometres away and can feedelectricity grids covering large areas. In 2008, a total of20,181 terawatt hours (TWh) of electricity were producedaround the world, most of which was generated fromthermal energy (fossil fuels of oil, coal and gas) (see Figure3.2 and Table 3.6). The world has a continued dependenceon these GHG-generating fuels. Although the relativereliance on fossil fuels for electricity generation declinedfrom 75.1 per cent in 1973 to 67.7 per cent in 2008, thetotal amount of energy produced from these sources grewfrom 4593TWh to 13,675TWh over the same period –recording an increase of 197.7 per cent.26 The IPCC FourthAssessment Report concluded that ‘the global energy supply


Figure 3.1

Global GHG emissionsby sector and enduse/activity

Notes: All data are for 2000. All calculations are based onCO2eq, using 100-year globalwarming potentials based onan IPCC total global estimateof 41,755 million tonnesCO2eq. Land-use changeincludes both emissions andabsorptions. Dotted linesrepresent flows of less than 0.1per cent of total GHGemissions.

Source: World ResourcesInstitute (http://cait.wri.org/figures/World-FlowChart.pdf)

Figure 3.2

World electricitygeneration by fuel type(1971–2008)

Note: ‘Other’ includes geothermal, solar, wind,combustible renewables andwaste, and heat.

Source: IEA, 2010, p24

GasEnd use/activitySector

EN

ER

GY

Transportation

Electricity and heat

Other fuelcombustion

Industry

Land-use change

Agriculture

Waste 3.6%

13.5%

18.2%

3.4%

10.4%

9.0%

24.6%

13.5%Road

AirRail, ship and other transport

Carbon dioxide (CO2)77%

Deforestation

Afforestation

Reforestation

Harvest/management

Other

Agriculture energy use

Agriculture soils

Livestock and manure

Methane (CH4)14%

Nitrous oxide (N2O)8%

HFCs, PFCs, SF61%

Fugitive emissions 3.9%

Industrial processes

Unallocated fuel combustion

Residential buildings

Commercial buildings

Iron and steel

Chemicals

Cement

Other industry

T&O leases

18.3%

–1.5%

–0.5%

2.5%

–0.6%

5.0%

3.8%

4.8%

3.2%

3.5%

5.4%

9.8%

2.3%1.6%

9.9%

Coal mining

Oil/gas extraction, refiningand processing

1.9%1.4%

6.3%

Aluminium, non-ferrous metals 1.4%1.0%1.0%1.0%

MachineryPulp, paper and printingFood and tobacco

1.4%

6.0%

5.1%

Rice cultivation 1.5%Other agriculture 0.9%Landfills 2.0%Wastewater, other waste 1.6%

Fossil thermal

19871983197919751971

TW

h

24,000

20,000

16,000

12,000

8000

4000

01991

Nuclear Hydro Other*

200319991995 2008

will continue to be dominated by fossil fuels for severaldecades’27 and projected that without the introduction ofeffective new policy actions, energy-related GHG emissionsare expected to rise by over 50 per cent between 2004 and2030 (from 26.1 billion tonnes CO2eq to between 37 and 40billion tonnes CO2eq).28

Electricity consumption varies significantly betweenurban areas around the world, although there is someclustering in the region of 4.5 to 7MWh per capita perannum for those connected to the grid: Bangkok (Thailand),Barcelona (Spain), Geneva (Switzerland), London (UK), LosAngeles (US), New York City (US) and Prague (CzechRepublic) all fall within this range. In contrast, Cape Town(South Africa) has considerably lower per capita consump-tion (3.49MWh per capita per annum – perhaps because alarge proportion of the population is not connected toelectricity supply); while Toronto (Canada) and Denver (US)have considerably higher per capita consumption of 10.04and 11.49MWh per capita per annum, respectively.29

The type of fuel used to generate electricity has asignificant impact upon the volume of GHG emissions.Indeed, this is one of the most striking features influencingthe emissions from different areas. Cities relying on nuclearor hydroelectric power generate substantially loweremissions than those that depend primarily on coal-firedpower stations.30

In countries relying heavily on coal for electricitygeneration, electricity can be the single largest contributorto GHG emissions. A study of 15 South African citiesindicated that electricity generation was responsible formore than 100 million tonnes of CO2 emissions annually, or66 per cent of the total – despite accounting for only 32 percent of energy consumption.31 However, average figures forelectricity consumption – and the GHG emissions relating to these – are problematic because of industrial use ofelectricity. More detailed surveys are required to identifywhich members of society are utilizing large quantities ofelectricity and, thus, are responsible for the accompanyingGHG emissions. In China, although the direct use of coal forenergy has declined substantially during the last twodecades, this remains the majority source for the generationof electricity.32

Among fossil fuels there are differences in theemissions generated for a given unit of electricity. Althoughcoal is the world’s most abundant fossil fuel and continues tobe a vital resource in many countries, the typical efficiencyof its conversion into electricity is about 35 per cent; and theburning of coal introduced approximately 9.2 billion tonnesof CO2 into the atmosphere in 2005. The use of natural gasfor electricity generation is growing rapidly (at an annual rateof 2.3 per cent during the 1990s), and contributes around5.5 billion tonnes of CO2 into the atmosphere each year. Incontrast, the use of oil for direct generation of electricity hasdeclined during recent years.33 The operation of nucleargeneration plants generates very low emissions of GHGs,although large indirect emissions are associated with themining (and refining) of uranium and the building of nuclearplants.34 This source of energy, however, has risks associatedwith its operation, storage of waste and the generation of

materials that can be used in nuclear weapons. For thesereasons, public acceptance of nuclear power is limited inmany countries.35

A variety of renewable energy systems can contributeto the security of energy supply and the reduction in GHGemissions (see Table 3.7).36 However, there are still manychallenges to be overcome in relation to the development ofthese technologies and in ensuring consistency in theirgeneration capacity. For example, energy available fromsolar, wind and wave energy varies over time.

Many developing countries still face considerablechallenges in expanding electricity networks to households –with low-income and female-headed households particularlyseriously affected. In South Africa, for example, 64 per centof the total population has no access to grid electricity.Although this is higher in rural areas, 16 per cent of house-holds in cities did not use electricity for lighting.37 Drawingon data for urban populations from a range of sources, it hasbeen estimated that among the 117 developing countries for

The type of fuelused to generateelectricity has asignificant impactupon the volume ofGHG emissions


Type of fuel Share of total energy generation (%)1973 2008

(total generation: 6116TWh) (total generation: 20,181TWh)

Thermal 75.1 67.8Coal/peat 38.3 41.0Oil 24.7 5.5Gas 12.1 21.3

Nuclear 3.3 13.5Hydro 21.0 15.9Other (geothermal, solar, wind, 0.6 2.8combustible renewable and waste, heat)

Source: IEA, 2010, p24

Examples of technology Stage of maturity

Large and small hydro Technologically mature with established markets Woody biomass combustion in several countries.GeothermalLandfill gas captureCrystalline silicon photovoltaic solar-water heatingOnshore windBio-ethanol from sugars and starchMunicipal solid waste to energy Technologically mature but with relatively new and Anaerobic digestion immature markets in a small number of countries.BiodieselCo-firing of biomassConcentrating solar dishes and troughsSolar-assisted air conditioningMini- and micro-hydroOffshore windThin-film photovoltaic Under technological development with Concentrating photovoltaic demonstrations or small-scale commercial Tidal range and currents application, but approaching wider market Wave power introduction.Biomass gasification and pyrolysisBio-ethanol from ligno-celluloseSolar thermal towersOrganic and inorganic nanotechnology solar cells Still in technology research stages.Artificial photosynthesisBiological hydrogen production involving biomass, algae and bacteria

Bio-refineriesOcean thermal and saline gradientsOcean currents

Source: compiled from Sims et al, 2007

Table 3.6

Electricity generationby energy source

Table 3.7

Categories of renewable energytechnologies

which data were available, there were 21 countries wheremore than half of urban households did not have access toelectricity. Furthermore, there seems to be a strong correla-tion between the proportion of the urban population whohave access to electricity and gross domestic product(GDP).38 Increasing low-income urban residents’ access toelectricity generates important improvements to quality oflife, including through reducing the use of potentiallyharmful or dangerous alternative fuels for heating, lightingand cooking. The provision of energy services – includingelectricity – is therefore an important component of alleviat-ing poverty.

Transport39

Globally, transportation is responsible for about 23 per centof total energy-related GHG emissions40 and 13 per cent ofglobal GHG emissions (see Figure 1.4). In addition, transportactivities increase as economies grow, and are expected tocontinue increasing in the decades ahead, especially withincreasing levels of urbanization. Urban areas rely heavily ontransportation networks of various kinds for both internaland external movements of goods and people. The propor-tion of journeys made by private as opposed to publictransportation – particularly in larger cities – is an importantfactor influencing GHG emissions from an urban area. Urbanareas, particularly in developed countries, often generatesmaller amounts of GHG emissions per capita than ruralareas due to the advantages of density. In the US, forexample, per capita gasoline consumption is 12 per centlower in urban counties than the national average.41

Increases in public transportation use tend to reduce GHGemissions. A recent study suggested that a 1 per centincrease in public transportation would lead to a 0.48 percent decrease in GHG emissions.42

Urban density is one of the most important factorsinfluencing the amount of energy used in private passengertransport, and therefore has a significant effect on GHGemissions. Table 3.8 shows the ranking of ten cities on thebasis of private passenger energy use, urban density andGHG emissions. With the exception of the Chinese cities,the most densely populated cities utilize less energy forprivate passenger transport and generally have lower GHGemissions per capita.

Access to public transport need not necessarily implyhigh density, as shown by the concepts of ‘transit-orienteddevelopment’ and ‘transit villages’ pioneered in California(US). These forms of development utilize moderate- to high-density housing within easy walking distance of major transitstops. However, this also requires careful planning of transitsystems, the formation of community partnerships, detailedunderstanding of local real estate markets, and coordinationamong local, national and regional authorities. If successful,these developments can provide mobility choices, increasepublic safety, reduce the number of vehicle kilometrestravelled (lowering annual household rates of driving by 20 to40 per cent for those living, working and/or shopping neartransit stations), reduce air pollution, reduce energy consump-tion, conserve resource lands and open space, reduce infra-structure costs, and contribute to more affordable housing.

Similar processes can be facilitated through the devel-opment of bus rapid transit systems in developing countries,which is discussed in more detail in Chapter 5. These aremost efficient in servicing densely populated linear develop-ments, which facilitate a large number of urban residentsliving within walking distances of the main trunk routes –generating an urban form often described as being shapedlike a hand with fingers (where the ‘palm’ is the urbancentre, and the ‘fingers’ the linear densely settled areasspreading out from the core).

Innovative thinking in relation to the planning oftransportation infrastructure can therefore meet bothenvironmental and social needs. Localized areas of relativelyhigh densities are required to generate greater efficiencies inthe usage of public transportation; but this can be consistentwith meeting a variety of other demands from urbanresidents. Of course, the precise form that these transporta-tion networks should take requires detailed local study.Overall, density is one of several factors that affects energyuse – and, by extension, GHG emissions. However, address-ing these issues requires ongoing analysis of urban processesrather than simply taking a snapshot of urban form at aparticular moment in time.

A key component of GHG emissions from transporta-tion is the number of vehicle kilometres travelled. Thenumber of vehicle kilometres travelled is affected by severalkey aspects of urban design, including:

• density (higher number of people, jobs and/or dwellingunits per unit area);

• diversity (greater mix of land uses);• design (smaller block sizes, more sidewalk coverage,

smaller street width);• destination accessibility; and• distance to transit.43

These ‘five Ds’ can be affected by the choices of plannersand developers, and, in turn, will affect the travel choices ofresidents living in these areas. These aspects of urban designintersect with issues of personal choice and economic neces-sity – for example, there is some evidence from Sweden thatwomen are more likely to use public transportation thanmen.44 Chapter 5 shows the ways in which efficient urban

The proportion ofjourneys made byprivate as opposedto public transportation … isan important factorinfluencing GHGemissions from anurban area

Innovative thinkingin relation to theplanning of transportation infrastructure can… meet bothenvironmental andsocial needs


Private passenger Urban density GHG emissions per capitatransport energy (descending order) (ascending order)per person(ascending order)

Shanghai (China) Seoul São PauloBeijing (China) Barcelona BarcelonaBarcelona (Spain) Shanghai SeoulSeoul (Republic of Korea) Beijing TokyoSão Paulo (Brazil) Tokyo LondonTokyo (Japan) São Paulo BeijingLondon (UK) London New York CityToronto (Canada) Toronto ShanghaiNew York (US) New York TorontoWashington, DC (US) Washington, DC Washington, DC

Source: compiled from Newman, 2006

Table 3.8

Private passengertransport energy use,urban density and GHGemissions, selectedcities

design – including the use of brownfield developments – canhelp to minimize the distances that urban residents have totravel and, hence, reduce GHG emissions.

However, a variety of other factors also affectemissions from ground transportation, including the extentof private motor vehicle use, the quality of public transport,land-use planning and government policy. As shown in Table3.9, there are significant variations between North Americancities as a result of these factors. For example, Denver’s percapita GHG emissions from ground transportation are fourtimes greater than those of New York. Similarly, the highlevel of private motor vehicle dependence in Bangkok meansthat its per capita emissions from ground transportation aretwice those of London, a much more affluent city but onewith a more comprehensive public transportation system.

These variations can also be seen in the proportion ofa city’s GHG emissions that can be attributed to the trans-port sector. Shanghai and Beijing generate approximately 11per cent of their emissions from the transportation sector, afigure dwarfed by their emissions from manufacturing.45

However, the emissions from transport are increasing rapidlyin Chinese cities, as shown by a recent study. The CO2emissions from transport in all 17 sample cities increasedbetween 1993 and 2006. On average, the increase between2002 and 2006 was 6 per cent per year and ranged from 2 to22 per cent between the sample cities. The CO2 emissionsper capita from transport also increased in all cities andranged between 0.5 and 1.4 tonnes per person in 2006,with Beijing being the highest.46

In London, New York and Washington, DC, trans-portation represents a significant contribution to the cities’emissions (22, 23 and 18 per cent, respectively); whereas inBarcelona (35 per cent), Toronto (36 per cent), Rio deJaneiro (30 per cent) and São Paulo (60 per cent), thesefigures are much higher.47 However, the high figures in Riode Janeiro and São Paulo are partially because these cities arestrongly reliant on private motor vehicle transportation Atthe same time, it should be noted that London’s emissionsfrom transportation are lower than most developed countrycities of similar size – as a result of high levels of publictransport usage, strong investment in infrastructure andpolicies to promote alternatives to private motor vehicle use– while the extensive public transport system in New YorkCity means that car ownership and usage levels are muchlower than those in the US as a whole. The contribution oftransportation to GHG emissions in Bangkok is described inBox 3.1.

Even when cars are chosen as the mode of transport,there are large variations in the GHG emissions produced bydifferent sizes and types of vehicles. Within conventionalprivate automobiles, there is a fourfold difference in theirGHG emissions per kilometre. More efficient engines andgreater use of diesel engines have the potential to reduceemissions. However, in the US, gains from engine efficiencyhave been offset as car weights and power have increased –meaning that overall fuel economy has hardly changed in thelast 15 years.48 Other factors that affect the contribution ofurban transportation to GHG emissions include vehicle tripfrequencies (starting a vehicle when it is cold uses more

energy and emits more CO2 than starting the vehicle after ithas warmed up) and vehicle operating speeds (motorvehicles with internal combustion engines are most efficientat an average speed of about 72km per hour). In spite ofthese issues, urban design that encourages less frequent caruse will generate far greater benefits than the small lossesassociated with engine start-up; and roadway design thatencourages higher speeds is likely to cause an increase indistances travelled by cars that will be far greater than anyefficiency benefits.49

There is a strong association between rising incomeand car use in developing countries, meaning that economicgrowth in developing countries is very likely to result inincreased car use and rising traffic congestion.50 In addition, inmany developing countries, the stock of motor vehicles is oldand consists largely of second-hand and less efficient vehiclesimported from developed countries. At the same time, theconversion of vehicles to use different fuels has the potentialto reduce GHG emissions in many cities in developingcountries. In Mumbai (India), for example, it has beenestimated that the conversion of more than 3000 diesel-fuelled buses to compressed natural gas would result in areduction of 14 per cent of total transport-related emissions.51

There is a strongassociation betweenrising income andcar use in developingcountries, meaningthat economicgrowth … is verylikely to result inincreased car use


City Gasoline consumption Diesel consumption GHG emissions (million litres) (million litres) (tonnes CO2eq

per capita)

Denver (US) 1234 197 6.07Los Angeles (US) 14,751 3212 4.74Toronto (Canada) 6691 2011 3.91Bangkok (Thailand) 2741 2094 2.20Geneva (Switzerland) 260 51 1.78New York City (US) 4179 657 1.47Cape Town (South Africa) 1249 724 1.39Prague (Czech Republic) 357 281 1.39London (UK) 1797 1238 1.18Barcelona (Spain) 209 266 0.75

Source: Kennedy et al, 2009b

Table 3.9

Ground transportation,fuel consumption andGHG emissions,selected cities

Box 3.1 The contribution of transportation to GHG emissions in Bangkok, Thailand

With approximately 7 million people, or more than 10 per cent of Thailand’s population,Bangkok is not only the national capital, but also its focus for communications, its administrativecentre and a major business hub for Southeast Asia. While the city’s population has grownrapidly during the last 50 years, the population of the inner city has been declining as peoplehave moved to suburban areas. Between 1978 and 2000, the population of the inner citydeclined from 3.25 million to 2.86 million, with a corresponding decrease in density from15,270 to 11,090 people per square kilometre. Per capita emissions from Bangkok are at asimilar level to many European and North American cities, with a figure of 7.1 tonnes per capitaper annum.

Transportation is the single greatest source of Bangkok’s GHG emissions, responsiblefor 23 million tonnes CO2eq per year, or 38 per cent of the city’s total. Electricity is the secondlargest contributor (33 per cent), followed by solid waste and wastewater (20 per cent). Thecontribution of this sector is growing rapidly: the number of vehicles registered in the city hassoared from 600,000 in 1980 to 5.6 million in 2007, an almost tenfold increase. Indeed, since2003, more than 500,000 additional vehicles have been registered in Bangkok each year.

Sources: Bangkok Metropolitan Administration, 2009; UN, 2010

The issue of emissions from transportation in develop-ing countries is particularly important in countries wheremotor vehicle ownership is expanding rapidly. There arecurrently (2011) nearly 1.2 billion passenger vehicles world-wide. By 2050, this figure is projected to reach 2.6 billion –the majority of which will be found in developingcountries.52 The emissions associated with the increase inpassenger vehicles can be reduced either through advancesin fuel technology or by changes from one mode of trans-portation to another. The potential for such reductions isparticularly strong in urban areas – with the advantage ofrelatively high densities of people, economic activities andcultural attractions. In Bogotá (Colombia), a bus rapid transitsystem (known as TransMilenio) – combined with car-restric-tion measures (including a path-breaking ‘car-free’ Sunday inwhich 120km of arterial roadways are closed to privatemotorized vehicles) and the development of new cycle-ways– has shown that an erosion of the relative importance of thepublic transport mode is not preordained.53 Similar systemshave also been proposed for several cities in Africa and Asia– for example, in Dar es Salaam.54

Current modes of urban transportation have manyother adverse effects. According to the World HealthOrganization, more than 1.2 million people were killed inroad traffic accidents in 2002. Projections indicate that thisfigure will increase by 65 per cent by 2020.55 Reducing thereliance on private motor vehicles may help to reduce thisfigure. In addition, heavy reliance on personal transportationresults in physical inactivity, urban air pollution, energy-related conflict and environmental degradation. Alternativemodes of transport – particularly walking and cycling – cangenerate co-benefits, including improved human healththrough reducing obesity alongside reduced GHG emis-sions.56 In addition, reducing the number of vehicles on theroad can reduce local-source air pollution which is directlylinked to mortality, cardiovascular diseases and respiratoryillnesses, including asthma among young children.57

Perhaps the most notable omission from the abovediscussion is emissions from the aviation industry, whichaccount for about 2 per cent of total anthropogenic GHGemissions.58 These are not included within a country’snational GHG inventory as a result of the lack of consensusas to where exactly these should be allocated. Should thesebe assigned to the country from which the aircraft takes off;the country in which the aircraft lands; the country inwhich the aircraft is registered; or the country of origin ofthe passengers? These issues are even more complex in thecase of city emissions, as many of the passengers usingmajor international airports situated in or close to majorcities may be from elsewhere in the country, or may only beusing these airports for transit purposes. The IPCC hasestimated that aviation is responsible for around 3.5 percent of human-induced climate change – the emissions fromhigh-flying aircraft cause a greater amount of warming thanthe same volume of emissions would do at ground level –and that this is growing by approximately 2.1 per cent peryear.59

Globally, shipping is responsible for about 10 per centof transportation energy use;60 but emissions from interna-

tional maritime transportation are not included withinnational GHG inventories for similar reasons. Although inter-national maritime transport is essential for servicing theneeds of urban areas, the role of urban centres as ports andtrans-shipment points means that allocating responsibilityfor the emissions associated with this is difficult, if notimpossible.

The GHG inventories produced by London and NewYork offer an alternative set of figures that do take emissionsfrom aviation into account. As a major air travel hub,London’s airports handle 30 per cent of the passengersentering or departing the UK. If incorporated within thecity’s emissions inventory, aviation would be responsible for34 per cent of London’s emissions, and would raise totalemissions from 44.3 million tonnes to 67 million tonnes for2006.61 In the case of New York (US), aviation would add10.4 million tonnes per year to the city’s emissions.62

However, as is the case with industrial emissions, allocatingthe responsibility for all aviation-based emissions to a city’sinventory is misleading – large city airports provide a servicenot only to individuals from elsewhere in the same country,but also from abroad.

Commercial and residential buildings

GHG emissions from commercial and residential buildingsare closely associated with emissions from electricity use,space heating and cooling. When combined, the IPCCestimates global emissions from residential and commercialbuildings at 10.6 billion tonnes of CO2eq per year,63 or 8 percent of global GHG emissions (see Figure 1.4). Commercialand residential buildings are responsible for both directemissions (onsite combustion of fuels), indirect emissions(from public electricity use for street lighting and other activ-ities and district heat consumption) and emissions associatedwith embodied energy (e.g. in the materials used for theirconstruction). Emissions are affected by the need for heatingand cooling, and by the behaviour of building occupants.

The type of fuel used for heating and cooling alsodetermines the amount of GHGs emitted. Although Praguein the Czech Republic uses less energy per capita for heatingthan New York City (US), its emissions from heating arehigher due to its reliance on coal. To a lesser extent, theemissions of Cape Town (South Africa) and Geneva (Switz-erland) are also slightly higher than other comparable citiesdue to the predominance of oil instead of natural gas forheating.64

Data are available for the US on the direct finalconsumption of fossil fuels in buildings and industry.65

However, it is not possible to separate the consumption offuel between residential, commercial and industrial uses.Natural gas and fuel oil are the primary sources of energy forheating these buildings, while electricity is the main sourceof energy for cooling. Consequently, urban areas in warmerclimate zones (where cooling, rather than heating, isrequired) tend to have lower direct final consumption offossil fuels, whereas the inverse is the case in cooler climatezones. However, there are also regional differences in fuelcomposition. The US Northeast relies more on fuel oil,

There are currently… nearly 1.2 billionpassenger vehiclesworldwide. By 2050,this figure isprojected to reach2.6 billion – themajority of whichwill be found indevelopingcountries.

GHG emissions fromcommercial andresidential buildingsare closely associated withemissions fromelectricity use, spaceheating and cooling

The type of fuelused for heating andcooling also deter-mines the amount ofGHGs emitted


which emits a greater volume of CO2 per unit of energy,while the US north Midwest relies more on natural gas.

The average size of new single-family homes in the UShas expanded during recent years. Larger houses occupymore land, require greater amounts of material for construc-tion, and consume more energy for heating and cooling.Larger homes are typically associated with higher incomesand higher energy consumption (see Table 3.10), and arefound more often in sprawling counties.66 Overall patternsof residential density also affect GHG emissions: the mostdensely settled area of the US (the Northeast, with 873persons per square kilometre) has the lowest per capitaannual energy consumption (283 million kilojoules), CO2emissions (15.0 tonnes) and vehicle distance travelled(13,298km) in the country.67

In the UK, residential buildings are responsible for 26per cent of all CO2 emissions, commercial and public build-ings for 13 per cent, and industrial buildings for 5 per cent.68

Most energy consumption (84 per cent) in residential build-ings is from the heating of space and water. As the primaryfuel for this is natural gas (which has a lower carbon contentthan electricity), this is only responsible for 74 per cent ofCO2 emissions. In non-residential buildings, heating (37 percent) and lighting (26 per cent) are the main sources of CO2emissions.

Estimates for residential energy use per unit area forthe UK and the US are 228 and 138kWh per square metreper year, respectively.69 Since the average dwelling size ismuch greater in the US (200 compared to 87 square metres),the US uses more energy per household. For non-residentialbuildings, energy use in the UK, the US and India are 262,287 and 189kWh per square metre per year, respectively.

In China, energy consumption of buildings accountsfor 27.6 per cent of national energy consumption andcontributes 25 per cent of national GHG emissions. In total,the country has 40 billion square metres of built space, ofwhich only 320 million square metres can be identified as‘energy-saving buildings’. The Energy Efficiency in Buildingand Construction programme aims to ensure that, by 2010,new urban buildings will reach a new design standard ofreducing energy consumption by 50 per cent.70 At a smallerscale, various initiatives are being implemented in othermiddle-income countries such as South Africa, including thedevelopment of low-cost, low-energy houses for the urbanpoor. These employ simple technologies such as north-facingorientation and roof overhangs to maintain comfortableindoor temperatures without the use of heating or coolingequipment.71

The growth in India’s population, coupled with therapidly increasing consumer expectations of its middle class,means that emissions from that country’s building stock arebecoming increasingly important. During 2005/2006, onlyabout 1 per cent of India’s urban households used electricityfor cooking, 59 per cent used natural gas or liquefied petro-leum gas, 8 per cent used kerosene, 4 per cent used coal orlignite, and the rest, about 27 per cent, used firewood,charcoal, biomass or other energy sources.72 Approximatelyone third of India’s energy is supplied by large hydropowerplants with limited GHG emissions. In the Indian residential

sector, fans account for 34 per cent of total electricityconsumption, lighting for 28 per cent and refrigeration for13 per cent.73 Of particular relevance for buildings in India isthe large amount of electricity used by heating, ventilationand air-conditioning systems. In buildings without this facil-ity, lighting is the main component of energy consumption,whereas in buildings with heating, ventilation and air-condi-tioning systems, these account for 40 to 50 per cent ofconsumption. However, there are large disparities betweenincome groups: low-income groups in urban areas relyheavily on kerosene and liquefied petroleum gas for energyalongside electricity, and a significant proportion still usefirewood or other biomass fuels. India’s commercial sectoruses electricity primarily for lighting (60 per cent ofconsumption) and heating, ventilation and air-conditioningsystems (32 per cent).74

Industry75

Globally, 19 per cent of GHG emissions are associated withindustrial activities (see Figure 1.4). Although most cities inNorth America and Europe emerged and developed as aresult of industrial activities, and still require industries toprovide jobs and revenue, these same activities generatepollution. However, during recent decades the global pattern of industrial activities has shifted, in part due totransnational corporations seeking lower wages and higherprofitability, and in part due to the increasing success ofcompanies and corporations from China, India, Brazil andelsewhere in competing on the world market. Differences inenvironmental legislation have also transformed the geogra-phy of industrial location. It has been noted that ‘when[cities] are able, they will get rid of polluting industries,pushing them away from city centers to suburbs or to othercities’.76

Many industrial activities are energy intensive in theiroperation. These include the manufacture of iron and steel,non-ferrous metals, chemicals and fertilizer, petroleum refin-ing, cement, and pulp and paper. There are differences inindustrial emissions according to location and according tothe size of the industry. In developing countries, some facili-ties are new and incorporate the latest technology. Yet, small-and medium-sized enterprises may not have the economic or technical capacity to install the latest energy-saving equipment. The industrial processes mentioned above areresponsible for direct GHG emissions. In Los Angeles (US),Prague (Czech Republic), and Toronto (Canada) these add0.22, 0.43 and 0.57 tonnes of CO2eq per capita per annum,respectively.77

Household income level Household area Energy consumption of (US$) (m2) household

(million kilojoules)

$15,000–$19,999 139.4 85$30,000–$39,999 157.9 92$75,000–$99,999 250.8 119$100,000 or more 315.9 143

Source: based on Markham, 2009, p12

Table 3.10

Energy consumption byincome level anddwelling size in the US(2008)

Larger houses …consume moreenergy for heatingand cooling

Differences inenvironmental legislation have alsotransformed thegeography of industrial location


A study of 15 South African cities shows that, onaverage, manufacturing caused half of all GHG emissions.However, in towns characterized as ‘heavy industrial’,manufacturing’s share rose to 89 per cent, and residentialshare declined to 4 per cent. This accounts for the extraordi-narily high per capita emission in some of these industrialtowns. Saldanha Bay (a large port and industrial centre inWestern Cape Province) and uMhlatuze (a port in KwaZulu-Natal that includes two aluminium smelters and a fertilizerplant) have per capita emissions of 50 and 47 tonnes of CO2 emissions per annum, respectively (see Table 3.13).However, 93 per cent of emissions from Saldanha Bay and 95per cent of emissions from uMhlatuze are generated byindustry and commerce, with households being responsiblefor only 1.9 per cent and 1.5 per cent of emissions, respec-tively.78

Similar patterns exist in China, where the ratio ofurban to rural per capita commercial energy usage is 6.8.79

This reflects a situation in which the industrial sector hastended to dominate urban CO2 emissions, although this hasbeen declining in some cases. Between 1985 and 2006, theshare of the industrial sector in total CO2 emissions fromBeijing declined from 65 to 43 per cent; and in Shanghaifrom 75 to 64 per cent. However, rather than representingan absolute decline, this reflects the growing significance ofthe transportation sector. CO2 emissions from transportationrose sevenfold in Beijing and eightfold in Shanghai over thesame time period. Another set of estimates suggests thatbetween 1990 and 2005, 90 per cent of Shanghai’s energywas consumed by the industrial sector and only 10 per centby ‘family life’, although these figures appear to excludeenergy consumption by transportation.80

Waste

Emissions from waste represent about 3 per cent of totalemissions (see Figure 1.4). Despite being only a smallcontributor to global emissions, rates of waste generationhave been increasing during recent years, particularly indeveloping countries that have been experiencing increasingaffluence. Although waste generation is linked to population,affluence and urbanization,81 emissions from waste may belower in more affluent cities, as urban areas have the poten-tial to greatly reduce – or even eliminate – emissions fromwaste. The concentration of people and activities in urbanareas means that waste can be collected efficiently, andmethane emissions from landfills can be captured and flaredor used to generate electricity. Although many developingcountries lack the technology for methane recuperation,landfill gas capture projects funded through the CleanDevelopment Mechanism (CDM),82 which are increasinglybeing implemented even in the least developed countries(e.g. at the Mtoni dumpsite in Dar es Salaam, Tanzania),offer numerous potentials.

As a result of some of the above-mentioned initiatives,GHG emissions from waste are relatively low in many urbanareas in developed countries. Per capita emissions fromwaste in Barcelona (Spain), Geneva (Switzerland), London(UK), Los Angeles (US), New York (US), Prague (CzechRepublic) and Toronto (Canada) are all less than 0.5 tonnesCO2eq per capita per annum; while those from Bangkok(Thailand) and Cape Town (South Africa) are 1.2 and 1.8tonnes CO2eq per capita per annum, respectively.83 Indeed,New York has negative net emissions as a result of thecapture of methane from managed landfills, while in SãoPaulo (Brazil), Barcelona (Spain) and Rio de Janeiro (Brazil)solid waste is responsible for 23.6, 24 and 36.5 per cent ofurban emissions, respectively.84 These variations are likely tobe due not only to different patterns of consumption andwaste generation, but also to differences in the managementof waste and differences in accounting mechanisms – varia-tions that are almost impossible to assess in the absence of astandardized urban framework for conducting emissionsinventories.

Agriculture, land-use change and forestry

At a global level, 14 per cent of GHG emissions can beallocated to activities related to agriculture and 17 per centto forestry (see Figure 1.4). Although these are oftenthought of as being rural activities, urban agriculture can bean important component of local economies and food supplysystems, and many urban areas do include parks and forests.The broader ecological impacts of cities have been increas-ingly studied during recent years,85 based on the recognitionthat the expansion of built-up areas transforms rural land-scapes; that city-based enterprises, households and instit-utions place demands on forests, farmlands and watershedsoutside urban boundaries; and that solid, liquid and airbornewastes are transferred out of the city to the surroundingregion or further afield.86

Specifically in relation to climate change, urban areascan shape emissions from agriculture, land-use change andforestry in two major ways. First, the process of urbanizationcan involve direct changes in land use, as formerly agricul-tural land becomes incorporated within built-up areas. Theworld’s urban population multiplied tenfold during the 20thcentury, meaning that more land was covered by urbandevelopment. Equally, global urban trends towards subur-banization mean that cities are sprawling and encroaching onland that may previously have been covered with vegetation– thereby reducing its potential to absorb CO2. Second, theconsumption patterns of increasingly wealthy urbanresidents can shape the type of agricultural activities that istaking place. For example, the growing consumption of meatproducts is associated with emissions of methane fromlivestock rearing.

Although wastegeneration is linkedto population, affluence and urbanization,emissions fromwaste may be lowerin more affluentcities, as urban areas have thepotential to greatlyreduce – or eveneliminate –emissions fromwaste

GHG emissions fromwaste are relativelylow in many urbanareas in developedcountries

Global urban trends towardssuburbanizationmean that cities aresprawling andencroaching on landthat may previouslyhave been coveredwith vegetation –thereby reducing itspotential to absorbCO2


THE SCALE OF URBANEMISSIONSIt is impossible to make definitive statements about the scaleof urban emissions. There is no globally accepted standardfor assessing the scope of urban GHG emissions – and evenif there was, the vast majority of the world’s urban centreshave not conducted an inventory of this type. Currentadministrative differences in the extent, frequency andthoroughness of inventories contribute to substantial varia-tions in the scope, accuracy and comparability of these.Perhaps the two most substantial differences between inven-tories are related to boundary issues and scope issues. Theseissues are discussed in greater detail in the next twosections.87 This section presents the results from a range ofpreviously conducted GHG inventories, assesses theirfindings, and identifies common themes across developedand developing countries.

Global patterns of emissions

The economic activities, behavioural patterns and GHGemissions from urban areas are shaped by the overalleconomic, political and social circumstances of the countriesin which they are located. At a global level, there are strikingdifferences in GHG emissions between regions and coun-tries. The 18 per cent of the world’s population living indeveloped countries account for 47 per cent of global CO2emissions, while the 82 per cent of the world’s populationliving in developing countries account for the remaining 53per cent. The US and Canada alone account for 19.4 percent of global GHG emissions, while South Asia accounts for13.1 per cent and Africa just 7.8 per cent.88 Even greaterdifferences can be seen if individual countries are compared:per capita CO2eq emissions vary from less than 1 tonne peryear for Bangladesh and Burkina Faso to more than 20tonnes for Canada, the US and Australia.89 These variationsamong countries are shown in greater detail in Figure 3.3.

In addition, global growth in GHG emissions has notbeen distributed evenly between countries. Between 1980

Per capita CO2eqemissions vary fromless than 1 tonneper year forBangladesh andBurkina Faso tomore than 20 tonnesfor Canada, the USand Australia


Figure 3.3

CO2 emissions percapita in selectedcountries and worldregions (2007)

Sources: based onhttp://mdgs.un.org/unsd/mdg(last accessed 21 October2010); and UN, 2010

QatarNetherlands Antilles, Kuwait

United Arab Emirates, BahrainUS

North AmericaAustralia

Canada, Saudi ArabiaEstonia, Kazakhstan

Finland, Czech Republic, SingaporeRussian Federation, The Netherlands

Republic of Korea, Japan, GermanyIsrael, Libya, Denmark

Norway, South Africa, UKEurope

Poland, Austria, ItalyEquatorial Guinea, Iran

Venezuela, France, Hong KongSweden, Switzerland, China

Argentina, Mexico, Romania, ChileThailand, Algeria, Turkey

Asia/PacificMauritius, Maldives, Korea DPR

Latin America & CaribbeanBotswana, Cuba, Tunisia, Egypt

Ecuador, PanamaBrazil, Uruguay

Costa Rica, IndonesiaPeru, Morocco, India

Colombia, Angola, BoliviaViet Nam, Moldova

AfricaTajikistan, Yemen, Guatemala

Pakistan, Swaziland, SamoaNicaragua, the Philippines, Zimbabwe

Paraguay, NigeriaMauritania, Sri Lanka

Papua New Guinea, Benin, SenegalGhana, Solomon Islands

Cameroon, Kenya, Sudan, BangladeshZambia, Togo, Liberia, Tanzania

Eritrea, Mozambique, Burkina FasoUganda, Ethiopia, Chad, Afghanistan

0 10 20 30 40

CO2 emissions (metric tonnes per capita) 2007

Average forleast developed countries

Average fordevelopingcountries

Average fordevelopedcountries

World average

50 60

and 2005, CO2 emissions increased by more than 5 per centper year in the Republic of Korea, China and Thailand. Yet,over the same period, emissions from Chad, the DemocraticRepublic of Congo, Liberia and Zambia declined by anaverage of more than 1 per cent per year.90 As these figuressuggest, many of the countries with currently very lowemissions are not experiencing rapid increases in emissions.However, if rapid economic growth takes place, this situationmay change. Various attempts have been made to compileGHG inventory figures for cities around the world. Datafrom two recent studies are presented in Tables 3.11 and3.12. The information in both tables is intended to be illus-trative of well-documented cases from a range of countries.One of the most striking features of these emissions invento-ries is that average per capita emissions for many large citiesare substantially lower than for the country in which theyare located (see Table 3.11; see also Table 3.5). For example,per capita emissions in New York City are 7.1 tonnesannually, compared to 23.9 tonnes for the US; those forLondon are 6.2 tonnes compared to 11.2 for the UK; andthose for São Paulo are 1.5 tonnes compared to 8.2 forBrazil. Although this is not a complete global analysis, itnonetheless suggests that – for a given level of economicdevelopment – urban areas offer the opportunity to supportlifestyles that generate smaller quantities of GHG emissions.

Urban emissions in developed countries

Many urban areas in developed countries have their origins(or their change in scale) in the industrial revolution and therapid expansion of manufacturing during the 18th and 19thcenturies. The industrial hubs of northern England, theRhine-Ruhr Valley in Germany and the north-eastern sea-board of the US all developed in close proximity to heavy rawmaterials such as coal and iron ore. However, since themiddle of the 20th century, the economies of these regionshave shifted away from secondary industry into tertiary andquaternary industries. As will be seen from the examplesdiscussed below, this means that their emissions from themanufacture of products are relatively low. At the same time,these urban areas have become centres of wealth andconsumption. The lifestyles of their residents – particularlyrelated to consumption and travel – generate a large carbonfootprint; yet this is seldom accounted for in emissionsinventories.

n Urban emissions in North AmericaToronto, Canada, was one of the earliest cities to recognizethe need to reduce CO2 emissions. In January 1990, the citycouncil declared an official target of reducing the city’s CO2emissions to 20 per cent below the 1988 level by 2005.91 Amore recent survey estimated per capita emissions of 8.2tonnes in 2001, compared to a Canadian average of 23.7tonnes (in 2004).92

A wide range of cities in the US have produced GHGinventories, although only a few of these are discussed hereto highlight particular issues. The overall per capita GHGemissions for Washington, DC, are relatively high comparedwith the other North American cities – with a value of 19.7tonnes CO2eq per capita each year, compared to a USaverage of 23.9 tonnes. Although Washington, DC, is adensely populated urban centre, with very little in the wayof industrial activities, it also has a relatively small population(572,059 in 2000) in relation to the large number of officesfor government and related functions, and large sections arevery wealthy. In this regard, it would have been more appro-priate (if data had been available) for comparative purposesto compare with the emissions from the entire Washington,DC, metropolitan area.93

New York City’s total GHG emissions were estimatedto be 61.5 million metric tonnes of CO2eq, which equates toper capita emissions of 7.1 tonnes in 2007 (see Figure 3.4).A detailed description of New York City’s contribution toGHG emissions is presented in Box 3.2. New York City’semissions are relatively low for a wealthy city in a developedcountry as a result of small dwelling sizes, high populationdensity, an extensive public transport system, and a largenumber of older buildings that emphasize natural daylightingand ventilation. Electricity accounts for about 38 per cent oftotal CO2eq emissions. The New York City electricity fuelmix is dominated by natural gas, but also includes coal, oil,nuclear and hydropower. Natural gas is also the dominantheating fuel and direct consumption of natural gas accountsfor 24 per cent of emissions.94

In the US as a whole, transportation is the largest end-use sector, accounting for 33.1 per cent of total emissions in


City GHG emissions per capita National emissions per capita(tonnes of CO2eq) (tonnes of CO2eq)

(year of study in brackets) (year of study in brackets)

Washington, DC (US) 19.7 (2005) 23.9 (2004)Glasgow (UK) 8.4 (2004) 11.2 (2004)Toronto (Canada) 8.2 (2001) 23.7 (2004)Shanghai (China) 8.1 (1998) 3.4 (1994)New York City (US) 7.1 (2005) 23.9 (2004)Beijing (China) 6.9 (1998) 3.4 (1994)London (UK) 6.2 (2006) 11.2 (2004)Tokyo (Japan) 4.8 (1998) 10.6 (2004)Seoul (Republic of Korea) 3.8 (1998) 6.7 (1990)Barcelona (Spain) 3.4 (1996) 10.0 (2004)Rio de Janeiro (Brazil) 2.3 (1998) 8.2 (1994)São Paulo (Brazil) 1.5 (2003) 8.2 (1994)

Source: Dodman, 2009

City Emissions per capita (tonnes of CO2eq per year)Emissions within city Direct emissions Life-cycle emissionsa

Denver (US) n/d 21.5 24.3Los Angeles (US) n/d 13.0 15.5Cape Town (South Africa) n/d 11.6 n/dToronto (Canada) 8.2 11.6 14.4Bangkok (Thailand) 4.8 10.7 n/dNew York City (US) n/d 10.5 12.2London (UK) n/d 9.6 10.5Prague (Czech Republic) 4.3 9.4 10.1Geneva (Switzerland) 7.4 7.8 8.7Barcelona (Spain) 2.4 4.2 4.6

Notes: n/d = not determined.

a Life-cycle emissions are associated with the transportation of goods and people outside city boundaries, and with theproduction of key urban materials, including food, water and materials for shelter, but that may not be directly emittedfrom within the cities’ geographical boundaries.

Source: Kennedy et al, 2009b

Table 3.11

Comparisons of cityand national GHGemissions, selectedcities

A wide range ofcities in the US haveproduced GHGinventories

Table 3.12

GHG emissions inventories, selectedcities

the country.95 Emissions from transportation in New YorkCity were 13 million metric tonnes of CO2eq during thefiscal year of 2007, or 22 per cent of the city’s total CO2eqemissions, which was well below the average for the US.96

Although the city’s official inventory did not include GHGemissions from aviation and shipping, emissions fromaviation have been estimated at 10.4 million metric tonnes,while emissions from transportation of freight by water havebeen estimated at 6.2 million metric tonnes.97 Residentialand commercial buildings each account for a larger share ofemissions than transportation, and, overall, buildingsaccount for 77 per cent of GHG emissions (although thisdoes include industry) (see Figure 3.4). The share of build-ing-sector emissions in New York City is larger than in theUS as a whole both because of reduced transportation-sectoremissions resulting from an effective public transit networkand because of the city’s large and energy-intensive commer-cial sector. Since buildings account for the majority ofemissions, this sector is likely to be the key focal point foremissions reduction policies in New York City.

As noted in Box 3.2, New York City has set a target ofa 30 per cent reduction in government operations emissionsby 2030.98 The GHGs emitted as a result of governmentoperations were 4.3 million metric tonnes CO2eq in 2007,representing approximately 7 per cent of the city-wide total.Similar to the city-wide results, buildings account for thevast majority of city government emissions (63 per cent).The city’s municipal vehicle fleet accounts for 8 per cent ofthe total.99

New York City’s 2007 city-wide inventory showedthat CO2eq emissions decreased by 2.5 per cent between2005 and 2007. Although energy consumption increasedbetween these two years, the carbon intensity of theelectricity supply decreased when two new efficient powerplants were introduced in 2006, displacing electricity gener-ated from less efficient plants with higher CO2eqcoefficients. This change alone reduced emissions by approx-imately 3.2 million metric tonnes (5 per cent reduction).Milder winter and summer weather conditions in 2007compared with 2005 also contributed to the reduction.‘Heating degree days’ and ‘cooling degree days’, whichreflect the demand for energy needed to heat or cool a homeor business, decreased by 0.6 and 17.7 per cent, respec-tively, from 2005 to 2007.100

A very different picture emerges from the emissionsinventory of Aspen, Colorado (US).101 The inventory givesan overall figure of 50 tonnes CO2eq per capita per annum,but also shows how various methods for calculation can leadto different results. Aspen is a major tourist destination, andthe figure includes a calculation to allocate emissions to thisgroup of temporary residents. If this is removed, then percapita emissions for the resident population rise to 102.5tonnes CO2eq. The overall figure includes air transportation– and if this is removed, as well as tourist driving andcommuting to locations outside Aspen, then the equivalentfigure falls to 40.3 tonnes CO2eq. Whichever figure is usedis considerably higher than the US national average, and thisindicates the high emissions from relatively small towns inpredominantly rural areas. Aspen is a very wealthy town witha high reliance on the tourism industry (which may be seenas energy intensive in its own right), and requires substantialheating because of its mountainous location.

A report by the Brookings Institution examines theper capita carbon footprints of individuals (rather thancomprehensive GHG inventories) from the 100 largestmetropolitan areas in the US from 2000 to 2005.102 The


New York City’s2007 city-wideinventory showedthat CO2eqemissions decreasedby 2.5 per centbetween 2005 and2007

Figure 3.4

GHG emissions inventory, New York City, US

Source: City of New York, 2009

2007 city-wide CO2eq emissions by sector 2007 city-wide CO2eq emissions by source

Total = 61.5 million metric tonnes

Buildings = 77%

Transportation = 22%

Other = 1%

Residential (32%)Commercial (24%)Industrial (12%)Institutional (9%)

Transit (3%)On-road vehicles (19%)

Methane (1%)

Diesel (3%)Distillate fuel oil (9%)Electricity (38%)Gasoline (17%)Kerosene (1%)Methane (1%)Natural gas (24%)Residual fuel oil (4%)Steam (3%)

Total = 61.5 million metric tonnes

Box 3.2 Contribution to GHG emissions, New York City, US

New York is the largest city in the US and a global centre of commerce and culture. The cityitself has a population of 8.25 million and forms the core of the New York Metropolitan Area,with a population of 18.8 million. The city produces approximately 8 per cent of total US grossdomestic product (GDP) and is a leading financial centre. In general, the city’s total emissionsare high, but per capita emissions are low in comparison to other urban areas in the US.

The city’s greenhouse gas (GHG) emissions are dominated by energy-related activities:more than two-thirds of the city’s emissions are associated with electricity and fuel consump-tion in residential, commercial and institutional buildings. A further 22 per cent is associatedwith transportation – this is low by US standards, as the city has the highest rate of commutingby public transport in the country. Three-quarters of the methane produced at landfills andwastewater treatment plants is captured, so this represents a very small source of emissions.

The City of New York has been completing GHG emissions inventories since 2007 andhas passed a law requiring annual updates to this. This is associated with PlaNYC: the mayor’scomprehensive sustainability plan for the city’s future, which has set goals including reducingGHG emissions by 30 per cent by 2030. Measures to achieve this are associated with upgradingthe local power supply (by replacing inefficient power plants with more advanced technologies),reducing energy consumption (by imposing more aggressive energy codes for new buildings andpromoting energy efficiency in existing buildings) and reducing transport-related emissions(through the expanded use of public transportation).

Sources: Parshall et al, 2009, 2010

report concludes that despite housing two-thirds of the USpopulation and three-quarters of its economic activity, thesemetropolitan areas emitted just 56 per cent of the country’sGHG emissions from highway transportation and residentialbuildings. However, the footprints that were assessed wereonly partial, and included only highway transportation andenergy consumption in residential buildings – and not emis-sions from commercial buildings, industry or non-highwaytransportation. Even within these parameters, there werelarge differences between metropolitan areas: from 1.36tonnes per capita in Honolulu (Hawaii, US) to 3.46 tonnesper capita in Lexington (Kentucky, US).

n Urban emissions in EuropeIn comparison to North American cities, the contribution ofurban areas in Europe to climate change is relatively low.This is as a result of several factors. European urban areastend to be more compact. They tend to have lower carownership and car usage rates, smaller, more fuel-efficientcars, reducing emissions from private transportation. Theytend to have more effective public transportation networks,which are deemed socially acceptable to a broader range ofindividuals. Furthermore, urban areas in Europe have higherlevels of densification and lower levels of sprawling inrelation to North American cities.

The overall CO2 emissions of London in 2006 were44.3 million tonnes – representing 8 per cent of the UK’stotal emissions, and a slight decline from the 45.1 milliontonnes produced in 1990 despite a rise in population of 0.7million people during the same time period.103 This reduc-tion can be attributed to the halving of industrial emissions,as industrial activity declined or has relocated to other partsof the UK or overseas. The per capita emissions from Londonare the lowest of any region in the UK, and at 6.2 tonnes percapita, in 2006, were just over half of the national average of11.2 tonnes per capita (see Table 3.11). Per capita emissionsfrom Glasgow at 8.4 tonnes per capita in 2004 are higherthan those for London; but this may also reflect the fact thatthe analysis covered the entire area of Glasgow and theClyde Valley, an area comprised of eight local authorities andcovering an area of 3405 square kilometres. This area alsoemits a higher than average quantity of agriculturalemissions due to a proportionally larger dairy farming sectorin the area.

Barcelona, the second largest city in Spain, had apopulation of 1.6 million people within its administrativeunit in 1996. Over the period of 1987 to 1996, the totalemissions for the city grew from 4.4 million tonnes to 5.1million tonnes. There was, however, a decline from 5.3million tonnes to 4.9 million tonnes between 1992 and1995. Part of this decline can be attributed to a decline inpopulation. Indeed, between 1987 and 1995, the populationof Barcelona shrank from 1.7 million to 1.5 million.Barcelona’s relatively low level of per capita emissions can beattributed to several factors. These include: the city’seconomy is primarily service based rather than manufactur-ing based; 90 per cent of the city’s electricity is generated bynuclear and hydro energy; the city’s mild climate and therarity of household air-conditioning systems; and the

compact urban structure, in which many residents live inapartments rather than individual houses.104

Given the reduced importance of manufacturing insome cities, some inventories have been produced that onlytake into account emissions associated with electricity, trans-portation and waste generation. In Oeiras municipality (partof the metropolitan area of Lisbon, Portugal, with a popula-tion of 160,000), electricity accounted for 75 per cent ofmunicipal emissions in 2003. Other sources of emissionswere gaseous fuel consumption (11 per cent), waste insanitary landfills (8 per cent), liquid fuels consumption (5per cent) and wastewater treatment (1 per cent). The totalmunicipal emissions in 2003 were 525,550 tonnes – or 3.3tonnes CO2eq per capita.105 Liquid fuels serve as a proxy for transportation. However, this only provides informationon the amount of fuel purchased, and not on the vehiclekilometres driven within the municipality. In addition, it failsto resolve important issues related to the allocation ofemissions from motor vehicles – whether these should fall inthe location of residence of the driver, the origin or destina-tion of any given journey, or some combination of the above.

Emissions inventories for Geneva, Switzerland, showannual within-city emissions of 7.4 tonnes CO2eq per capita,and for Prague, Czech Republic, show annual within-cityemissions of 4.3 tonnes CO2eq per capita. If ‘life-cycle’emissions are taken into account, these figures rise to 8.7and 10.1 tonnes CO2eq per capita, respectively (see Table3.12).

Urban emissions in developing countries

Very few detailed emissions inventories have been producedby cities in developing countries. Cities in these countriesare frequently economic centres that contribute significantlyto the gross national product (GNP), and act as economic,political, social and cultural centres. Consequently, thesecities are centres of consumption and wealth, with likelyconsequences including higher per capita GHG emissionsthan surrounding areas.

As manufacturing has declined in importance in devel-oped countries, it has expanded rapidly in some developingcountries. Countries such as Brazil, China, India and SouthAfrica – encouraged by economic and geopolitical changes –are now centres for global manufacturing. The relativelycheap and plentiful supply of labour, and the increased easeof transporting raw materials and finished products, meansthat these countries can compete effectively on the worldmarket. Yet, this competition is not without costs, some ofwhich are associated with local environmental degradationand others with the emission of GHGs. Current global proto-cols for measuring emissions, and setting targets for theirreduction, solely address the location of production of theseGHGs, which means that some developing countries withprospering manufacturing industries appear to be majoremitters.

Some developing countries play an increasinglyimportant role in contributing to global GHG emissions.China has recently overtaken the US as the world’s leadingtotal emitter of GHGs, although its per capita emissions are

In comparison toNorth Americancities, the contribution ofurban areas inEurope to climatechange is relativelylow

Very few detailedemissions invento-ries have beenproduced by cities indeveloping countries

China has recentlyovertaken the US asthe world’s leadingtotal emitter ofGHGs, although itsper capita emissionsare significantlylower


significantly lower.106 Brazil, China, India and South Africatogether form the ‘BASIC’ group of countries that – althoughnot part of the legally binding framework to reduce emis-sions – recognize that their substantial emissions compelthem to take a more progressive role in international climatenegotiations. Specifically, these countries are at the fore-front of the development of ‘nationally appropriatemitigation actions’107 and the reduction in carbon intensityof their industries, rather than absolute reductions inemissions.

Box 3.3 provides an overview of the GHG emissionsfrom São Paulo, Brazil. As indicated, total annual emissionsfrom São Paulo are 15.7 million tonnes, or 1.5 tonnes percapita. However, there is the potential for the transportationand solid waste sectors in the city to engage in GHG mitiga-tion activities – for example, through CDM projects such asthe landfill gas to energy project at Bandeirantes.

GHG emissions have also been calculated for MexicoCity, although the figures generated vary widely: from a totalof 34.9 million tonnes CO2eq in 1996 to 60.0 million tonnesin 2000, and 62.6 million tonnes in 2004. This variation is aresult of the scarcity and inconsistency of official invento-ries, and methodological issues related to the inclusion andexclusion of emissions from solid waste and aviation.

However, even at the higher level this equates to per capitaemissions of 3.6 tonnes per year, lower than the nationalfigure of 4.6 tonnes.108 Box 3.4 provides further insights onGHG emissions for Mexico City.

In South Africa, CO2 emissions have been calculatedfrom six large metropolitan areas (‘metros’), four industrialtowns/cities and five non-industrial towns/cities (see Table3.13). The average annual per capita emissions from all theseurban areas is 8.1 tonnes of CO2. This is slightly lower thanthe national average of 8.9 tonnes, but considerably higherthan the African average of 1.1 tonnes. When broken downaccording to type of town, ‘non-industrial towns and cities’have average per capita emissions of 3.4 tonnes; ‘metros’,6.5 tonnes; and ‘industrial towns and cities’, 26.3 tonnes.The averages for individual urban areas range from 1.7tonnes for King Sabata to a massive 49.5 tonnes for SaldanhaBay. The main sources of these emissions also vary substan-tially. In industrial towns, manufacturing accounts for asmuch as 89 per cent of the emissions, while in non-industrialtowns, this figure was only 36 per cent. This is reflected inthe CO2 emissions per economic unit of value added, whichshows that this is much higher in industrial centres than inservice-oriented cities. Thus:

Brazil, China, Indiaand South Africa …are at the forefrontof the developmentof ‘nationally appropriate mitiga-tion actions’ and thereduction in carbonintensity of theirindustries, ratherthan absolute reductions inemissions


Box 3.3 Contribution to GHG emissions, São Paulo, Brazil

The São Paulo Metropolitan Region has a population of 18 million and is the largest urban area in Brazil. The city is a major driving force forthe national economy, with a gross domestic product (GDP) of US$83 billion in 2003. The service industry is the main driver, accounting for62.5 per cent of GDP. This is followed by the industrial sector, which accounts for 20.6 per cent.

A comprehensive greenhouse gas (GHG) emissions inventory was conducted in 2005. It shows that energy use accounts for morethan three-quarters of the city’s emissions (see figure below). Approximately two-thirds of this was associated with diesel and gasoline, and11 per cent with electricity generation. However, the contribution of urban transportation to GHG emissions is still relatively low as a resultof the mandatory blend of ethanol (23 per cent) and gasoline (77 per cent) used in most of the private fleet. Similarly, the contribution of theelectricity generation sector is low as the city relies heavily on hydroelectric generation. Solid waste disposal accounted for almost onequarter of the city’s emissions, or 3.7 million tonnes of CO2eq. However, Clean Development Mechanism (CDM) projects at the Bandeirantesand São João landfills will prevent the generation of 11 million tonnes of CO2eq by 2012 – almost removing the contribution of solid waste tothe city’s emissions.

Per capita emissions from the city are low, atabout 1.5 tonnes CO2eq per year (in 2003), compared toa national average for Brazil of 8.2 tonnes (1994 figure).Despite this, the growing importance of reducing globalGHG emissions means that cities in middle-incomecountries will increasingly need to identify their emissionsreduction potential and act on this.

It is important to note that although the city ofSão Paulo accounts for 6.8 per cent of the population ofBrazil, its GHG emissions are relatively small. This isbecause Brazil is a large emitter of GHGs from agricul-ture, land-use change and forestry. In the case ofdeforestation, due to high rates, emissions account for63.1 per cent of total national emissions of CO2 andmethane. The agriculture sector as a whole is responsiblefor 16.5 per cent of the same gases, mainly because of thesize of the national herd. In the case of the extremelyurbanized city of São Paulo, these emissions are insignificant.

Sources: Dubeux and La Rovere, 2010; La Rovere et al, 2005; Ministério da Ciência e Tecnologia, 2004

Wastewater treatment (<0.1%, 7400 tonnes)

Solid waste disposal(23.5%, 3,696,000 tonnes)

Land use change(0.3%, 51,400 tonnes)

Agriculture(<0.1%, 800 tonnes)

Energy(76.1%, 11,985,500 tonnes)

Assessments and comparisons done using theCO2/unit of economic value created have to beviewed with caution. Because of economiclinkage between cities, economic value createdwith relatively low CO2 emissions in one citymight depend on the economic value createdwith much higher emissions in another. Forexample, while the City of Johannesburg meas-ures 9.6 tonnes CO2/R100,000 [South Africanrand] compared with 133.6 tonnes CO2/R100,000 for Sedibeng, the City of Johan-nesburg derives components of its economic

value creation through provision of low-energy-intensity services to high-energy-intensity indus-tries in Sedibeng … the cities cannot be seen inisolation.109

Further assessment of Cape Town’s GHG emissions showsthat electricity use is responsible for 69 per cent ofemissions (see Box 3.5). This high level of emissions isrelated to the fact that 95 per cent of South Africa’s electri-city generation is coal fired, with high levels of emissions forgiven quantities of energy. By sector, transport accounts for54 per cent of energy use, followed by commerce and indus-


Box 3.4 GHG emissions and climate change in Mexico City

Mexico City has one of the highest levels of air pollution in the world. With anestimated population of 20.1 million people, 3.75 million cars and 35,000 indus-tries, the Mexico City Metropolitan area is a major emitter of greenhouse gases(GHGs). In 2007, its emission was estimated at 60 million tonnes of CO2eq,accounting for 9.1 per cent of national emissions. Of these, 37 million metrictonnes of CO2eq were produced within Mexico City, with transportation, indus-try, housing and solid waste management serving as the major contributors (43,22, 13 and 11 per cent, respectively). About 88 per cent of all GHG emissions inMexico City are attributed to energy consumption in the form of fossil fuels andelectricity used in transportation, industry, trade, housing or services.

The Mexico City government recognizes that climate change is now themost serious threat to the ecosystems of the city, with unquestionable socio-economic consequences for the population. Consequently, the city hasdeveloped the Mexico City Climate Action Programme 2008–2012, with a totalof 26 GHG mitigation actions. If implemented, they will reduce the CO2eqemissions by 4.4 million tonnes a year, which represents 12 per cent of theannual GHG emissions in Mexico City.

Sources: Delgado, 2008; Casaubon et al, 2008

Box 3.5 Contribution to GHG emissions, Cape Town, South Africa

With a population of about 3.2 million people, the City of Cape Town accountsfor 5 per cent of South Africa’s total energy consumption and 5.2 per cent ofthe national electricity consumption. Greenhouse gas (GHG) emission from fueltypes used in the city has been significant, with electricity accounting for 69 percent; petrol, 17 per cent; and diesel, 9 per cent. Other fuels (paraffin, liquid petro-leum gas, coal, heavy furnace oil and wood) account for the rest.

The city’s energy and climate strategy identifies industry, transport andresidential as the major sectors contributing to GHG emissions both within theCity of Cape Town and in the entire Western Cape region. As a result, the Cityof Cape Town has an average annual emission of 6.4 tonnes of CO2 per person(compared to Western Europe at 4.5 tonnes, and the rest of Africa at 0.6tonnes). The emissions cause visible pollution (‘brown haze’). In 2003, air qualitymonitoring stations recorded 162 days of poor air quality. An earlier Cape TownBrown Haze Study, conducted in 1997, attributed 65 per cent of the brown hazeto vehicular emission, of which 49 per cent is caused by diesel vehicles and 16per cent by petrol vehicles.

Sources: City of Cape Town, 2006, 2007

Town/city Population Total CO2 emissions CO2 per capita CO2 per 100,000 South (tonnes) (tonnes) African rand value added*

City of Cape Town 3,069,404 19,736,885 6.4 13.7City of Johannesburg 3,585,545 19,944,863 5.6 9.6City of Tshwane 1,678,806 13,537,109 8.1 12.7Ekurhuleni 2,761,253 22,917,257 8.3 24.9eThekwini 3,269,641 18,405,182 5.6 15.6Nelson Mandela 1,013,883 4,754,204 4.7 13.8Total for ‘metros’ 15,378,532 99,295,500 6.5 14.1uMsunduzi 562,373 3,543,806 6.3 N/ASaldanha Bay 79,315 3,923,771 49.5 30.2Sedibeng 883,772 25,257,942 28.6 133.6uMhlatuze 360,002 16,816,074 46.7 140.1Total for ‘industrial towns/cities’ 1,885,462 49,541,593 26.3 123.1Buffalo City 702,671 2,449,144 3.5 106.9King Sabata 421,233 713,526 1.7 N/AMangaung 662,063 2,495,297 3.8 16.7Potchefstroom 129,075 634,580 4.9 15.4Sol Plaatje 196,846 882,234 4.5 13.9Total for ‘non-industrial towns/cities’ 2,111,888 7,174,781 3.4 15.7Total for towns/cities reviewed 19,375,882 156,011,874 8.1 13.0Total for South Africa 46,586,607 391,327,499 8.4 N/A

Notes: * In 2004, US$1 was worth an average of 6.5 South African rand. N/A = not available.

Source: Sustainable Energy Africa, 2006

Table 3.13

CO2 emissions fromSouth African urbanareas (2004)

try (29 per cent), residential (15 per cent) and local author-ity (2 per cent).110

It needs to be emphasized that the responsibility forthese emissions is not distributed evenly throughout theurban population. While more affluent urban residentsconsume resources – including fuel for heating or cooling,petrol or diesel for transportation, food items and consumergoods with high levels of ‘embedded carbon’ – in similarquantities to urban residents in developed countries, poorerurban residents use very little of these resources. Althoughthis is an issue in all urban centres, it is particularly evidentin highly unequal societies.

A recent study in India showed that the average GHGemissions of the wealthiest 1 per cent of the Indian popula-tion are 4.52 tonnes CO2eq per annum, or more than fourtimes as much as the 1.11 tonnes CO2eq per annum gener-ated by the poorest 38 per cent of the population.111 Asignificant proportion of urban residents in low-incomecountries have very low levels of GHG emissions because oftheir limited use of fossil fuels, limited use of electricity, andlimited consumption of goods and services that require GHGemissions for their production and transportation. Indeed,many low-income urban dwellers whose livelihoods arebased on reclaiming, reusing or recycling waste may actuallygenerate negative emissions through these activities.112

Various efforts are being made to reduce greenhousegas emissions in urban areas in low-income countries,frequently in association with broader goals of improving airquality and implementing more effective solid wastemanagement. In Dhaka (Bangladesh), motorized rickshawshave been banned from using two-stroke petrol enginessince September 2002 and have been replaced by enginesusing compressed natural gas.113 Although introduced more

as a measure to improve local air quality, compressed naturalgas engines can reduce lifetime greenhouse gas emissions by 21 to 26 per cent.114 Similarly, a range of interventionsdeveloped for the Dhaka Metropolitan DevelopmentPlanning Support System – including environmental andphysical quality, urban and infrastructure development,social and economic development, governance, and educa-tional and scientific development – have relevance to climatechange mitigation efforts.115

Estimating the global-level urban emissions

Any blanket statements about the total contribution of urbanareas or cities to GHG emissions need to be treated withcaution. There is no globally accepted definition of an urbanarea or city, and there are no globally accepted standards forrecording emissions from sub-national areas. In addition,there is little clarity on the relative allocation of responsibil-ity from production- or consumption-based approaches. Thisis made particularly clear in the South African casespresented above, as well as in the comparison betweenJapanese and Chinese cities in which vastly different propor-tions of emissions can be attributed to the manufacturingsector, which produces goods for consumption in manyother locations around the world.

At one extreme, it could be argued that urban areasmake no contribution to GHG emissions: that the economicand social benefits, and environmental costs, associated withtheir commercial, industrial and manufacturing sectors aredistributed more widely to individuals throughout countries,regions and around the world. In this regard, individuals orsectors could be deemed ‘responsible’ for certain levels ofemissions. At the other extreme, it could be argued that all

A significant proportion of urbanresidents in low-incomecountries have verylow levels of GHGemissions

Any blanket statements aboutthe total contribution ofurban areas or citiesto GHG emissionsneed to be treatedwith caution


Sector Percentage of Justification for estimating the proportion of GHGs from cities, Percentage of GHGs global GHG emissions from the perspective of the location of activities that produced them allocated to cities

Energy supplya 25.9 A high proportion of fossil fuel power stations are not in cities, especially 8.6–13.0the largest cities.One third to one half of emissions from city-based power stations.

Industry 19.4 A large proportion of heavy industry (which accounts for most GHGs from 7.8–11.6industry) is not located in cities, including many cement factories, oil refineries, pulp and paper mills, metal smelters.Two-fifths to three-fifths of emissions in cities.

Forestryb 17.4 No emissions assigned to cities. 0Agriculture 13.5 Some large cities have considerable agricultural output, but mostly because 0

of extended boundaries encompassing rural areas. No emissions assigned to cities.

Transport 13.1 Private use of motor vehicles a large part of this. Should commuting by car 7.9–9.2by those living outside cities be assigned to cities? Should city dwellers driving outside city boundaries be assigned to their city?60 to 70 per cent of emissions assigned to cities.

Residential and 7.9 Large sections of middle- and high-income groups in developed countries 4.7–5.5commercial buildings live outside cities – and a significant and increasing proportion of commercial

buildings are located outside cities.60 to 70 per cent of emissions assigned to cities.

Waste and wastewater 2.8 More than half of this is landfill methane; but a proportion of this would 1.5be released outside urban boundaries from waste generated inside cities. 54 per cent of emissions assigned to cities.

Totalc 100 30.5–40.8

Notes: a A large part of this is from fossil fuel power stations. Excludes refineries, coke ovens, etc., which are included under industry.b Land use and land-use changes. c Total emissions for the GHGs covered by the Kyoto Protocol amounts to 49 billion tonnes of CO2eq.

Sources: based on Barker et al, 2007; Satterthwaite, 2008a, p544

Table 3.14

Cities’ contribution toglobal anthropogenicGHG emissions, bysector

human activities other than those directly associated withrural land-use change and agriculture are urban in theircharacter. In this situation, all non-forestry and agricultureemissions could be allocated to urban areas – which consti-tute 69 per cent of total global emissions according to theIPCC. Neither of these perspectives is valid – but they dohighlight that ‘drawing the line’ as to exactly how urbanareas ‘contribute’ to climate change is a highly subjectiveprocess.

From the perspective of the location of production, ithas been suggested that cities (in this case, excluding smallertowns and other small urban settlements) probably emitbetween 30 and 40 per cent of all anthropogenic GHGemissions (see Table 3.14). This is based on an analysis of thecontribution of different sectors to global emissions, and anassessment of the proportion of each of these that is associ-ated with cities.116 Table 3.15 provides higher estimates ofthe contribution of cities to global GHG emissions,117

although, in this case, cities refer to all urban areas, includ-ing towns and other small urban settlements. It has beensuggested that various overestimates of urban contributionsto climate change are related to an Organisation forEconomic Co-operation and Development (OECD) report,which states that 80 per cent of global energy use is linkedto cities.118 Consequently, a production-based figure of 40 to70 per cent, and a consumption-based figure of 60 to 70 percent has been presented.119 The differences betweenconsumption- and production-based approaches will bediscussed in greater detail below.120

FACTORS INFLUENCINGEMISSIONSAs the previous section showed, the contribution of urbanareas to GHG emissions in different countries – and even ofdifferent urban areas within the same country – variesgreatly. This is due to a variety of factors, including differ-ences in the sources of emissions.121 This section examinesthe main factors that affect the sectors generating GHGs –namely, geographic situation, demographic variation, urbanform and the types of economic activities. None of thesefactors operate in isolation, and it is perhaps more appropri-ate to conceptualize the urban system as a whole –recognizing that any urban area is intricately linked withrural areas, urban areas within the same country, and hasinternational linkages. The discussion also looks at thepolitics of measuring GHG emissions by discussing alterna-tive approaches, such as ecological versus carbon footprints,production-based versus consumption-based approaches,and individual versus urban drivers of emissions.

Geographic situation

Various aspects of geography affect the contribution of urbanareas to climate change. These can be broadly categorized asclimatic situation, altitude and location in relation to naturalresources. The climatic situation of any given urban areaaffects the energy demands for heating and cooling. High-latitude locations have longer hours of darkness in the winter,requiring additional energy consumption for lighting. High-latitude locations are also colder in winter, with additionalheating requirements. Both space and water require heating,and in many countries (e.g. the UK), the heating of water is amajor consumer of energy in residential households. Heatingrequirements are usually met through the direct burning ofan energy source such as coal, oil or natural gas. In contrast,space cooling through air conditioning is normally poweredby electricity. Urban areas in warmer locations therefore havean emissions profile strongly influenced by the energy sourceused to generate this.

In Spain, electricity demand shows an increasingtrend that can be linked to demographic, social andeconomic factors. Within this trend, variations in consump-tion can be seen as a result of particular weather conditions.In the winter months, colder than normal days are associatedwith increased electricity consumption for heating, whereasin the summer months, warmer than normal days are associ-ated with this for cooling.122

In the US, the consumption of fuel oil and natural gasby households is determined primarily by climate. There is avery strong negative correlation between home heating-related emissions and lower temperatures in January – afactor that is, itself, determined by geographical location.123

In contrast, many locations in the US with particularly hotsummers (higher temperatures in July) have higher electri-city consumption associated with space cooling. Solelytaking these issues into account, it has been noted that areaswith moderate temperatures have lower emissions and lowerassociated expenditure on energy. Although comparablestudies have not been undertaken elsewhere, it is likely thatthis pattern is replicated on a global level, with areas experi-encing very hot or cold climatic conditions requiring agreater use of energy for the cooling or heating of residentialand commercial buildings.

The geographical location in relation to naturalresources influences the fuels that are used for energygeneration and, hence, the levels of GHG emissions. This is afactor of transportation costs: where a more efficient sourceof fuel is available in close proximity to the city or town, itcan be used more economically. For example, urban areasthat are able to draw on nearby sources of natural gas willemit a smaller volume of GHGs for a given amount of energythan areas that rely on coal for energy. China’s continuedreliance on coal, which provides 70 per cent of its totalenergy requirements, is largely due to the abundance of thisresource – China has the world’s third largest coal reservesand is the largest coal producer in the world. In contrast,countries with larger reserves of natural gas tend to be morereliant on this cleaner source of energy. For example, the UKhas increased the proportion of its energy from natural gasfrom 20 to 34 per cent between 1980 and 2003.124

The climatic situation of anygiven urban areaaffects the energydemands for heatingand cooling

The geographicallocation in relationto natural resourcesinfluences the fuelsthat are used forenergy generationand, hence, thelevels of GHGemissions


Cities’ share in … 2006 2030(%) (%)

Global energy consumption 67 73Global energy-related CO2 emissions 71 76Global anthropogenic GHG emissions 40–70 43–70

Source: Walraven, 2009

Table 3.15

The contribution ofurban areas to variousaspects of climatechange

The potential for using renewable sources of energy –and the reductions in GHG emissions associated with this –are also affected by locational factors. Some renewableenergy is entirely reliant on natural resources – for example,the availability of large rivers for hydroelectric generation:Rio de Janeiro and São Paulo (in Brazil) have low levels ofemissions from electricity generation for this reason. Inother locations, particularly in smaller or more arid regions,large-scale hydroelectric generation is not a viable source ofenergy. Wind, geothermal, tidal and wave energy all rely onnatural phenomena existing in particular locations, althoughsolar photovoltaic and solar thermal energy are less tied tospecific locations.125

Geographical location affects the type of economicactivities taking place in urban areas. Similarly, these canboth be environmental and social factors of location.Historically, heavy industry has been located close to bulkyraw materials, particularly coal and iron ore. The new inter-national division of labour, coupled with increasingreductions in cross-border tariffs, means that spatial varia-tion in the cost of labour are increasingly important indetermining the location of manufacturing activities.

The geographic level at which decisions on energy aremade can also influence emissions from urban areas.Decisions to construct and operate nuclear power plants aremade at the country level, rather than at the city level.Nuclear power generation – assessed purely from a GHGemissions perspective – enables reduced climate impactsfrom a given amount of energy; yet urban areas themselvesare unable to make decisions of this nature. National policydecisions in France and Spain are one reason why cityemissions in these countries are lower than those of cities inthe UK.

Demographic situation

The relationship between population growth and GHGemissions is complicated, and varies according to the level ofanalysis. As can be seen from the wide variations in GHGemissions from countries around the world, population sizein itself is not a major driver of global warming. At a globallevel, the areas experiencing the highest rates of populationgrowth are areas with currently low levels of per capitaemissions. As Table 3.16 shows, the developing countrieswith the highest rates of population growth have had muchlower rates of growth in their CO2 emissions than developedcountries with much lower rates of population growth.While larger urban populations do lead to increased totalsulphur dioxide emissions and transportation energy use,126

there is no evidence to suggest that this results in higher percapita emissions. Table 3.16 also shows that the increase inCO2 emissions in high-income countries has been signifi-cantly higher than in the upper-middle income countries,despite relatively similar rates of population growth.

The demographic composition of a society has a widerange of effects on consumption behaviour and GHGemissions. In some urban areas, changing age structures willaffect GHG emissions associated with energy use. Populationaging in the US has been shown to cause reductions in

labour income and changes in consumption patterns – bothof which result in lower GHG emissions. Depending on thefactors taken into consideration, these savings can rangefrom 15 to 40 per cent of the emissions that would other-wise be expected. Conversely, in China, estimates of GHGemissions that incorporate aging suggest that this willinitially lead to higher emissions (as the proportion of thepopulation in the labour force and, hence, their power toconsume increases), followed by reduced emissions (as thisproportion declines).127

Another demographic change that may affect patternsof GHG emissions from urban areas is the increasing trendtowards smaller households. In many developed countriesand some developing countries such as China, the averagehousehold size has declined – meaning that the number ofhouseholds has expanded more rapidly than the total popula-tion size. Economies of scale are therefore reduced, with theresult that the per capita energy consumption of smallerhouseholds is significantly higher than that of larger house-holds.128

Paradoxically, the slowing of population growth mayresult in increased emissions, as lower population growth andsmaller household sizes may be associated with a rise in thenumber of separate households and increased disposableincome to be spent on consumption. The decline in fertilityin Brazil has been associated with a rapid rise in the numberof households. The total fertility rate declined from six birthsper woman during the mid 1960s to replacement level in themid 2000s. While the population grew at an annual rate of1.4 per cent between 1996 and 2006, the actual number ofhouseholds increased at an annual rate of 3.2 per cent. Overthe same time period, the number of ‘double income no kids’households almost doubled (from 1.1 million to 2.1 million).These households have relatively high incomes and the abilityto consume larger quantities of goods and services withassociated consequences for their total GHG emissions.129

The relationship between population size, populationcomposition and the contribution of urban areas to climate change is therefore complex. As cities grow, they concentrate the demand for fresh water and other naturalresources, and concentrate the production of pollutants andGHGs. Cities with considerable local ecological impact –such as Solapur, India, with 1.1 million people but lowaverage consumption – may have much smaller globalimpacts than similar-sized cities (such as Perth, Australia, orPortland, US). These latter cities have moderated their localecological impact by importing most of the goods that theyconsume – potentially producing far larger global impacts.130

Per capita energyconsumption ofsmaller householdsis significantlyhigher than that oflarger households

Paradoxically, theslowing of population growthmay result inincreased emissions,as lower populationgrowth and smallerhouseholds sizesmay be associatedwith a rise in thenumber of separatehouseholds andincreased disposableincome to be spenton consumption


Income category in 2005 1950–1980 1980–2005Growth in Growth in CO2 Growth in Growth in CO2population emissions population emissions

(%) (%) (%) (%)

Low-income countries 36.0 5.6 52.1 12.8Lower-middle income countries 47.1 39.7 35.7 53.2Upper-middle income countries 5.7 9.6 5.0 5.0High-income countries 11.2 45.1 7.2 29.1

Source: Satterthwaite, 2009, p558

Table 3.16

CO2 emissions, population growth andnational income

Taking this into account, it is not the absolute number ofpeople who live in urban areas that affects the contributionof these areas to climate change. Rather, it is the way inwhich these areas are managed, and the choices that aremade by the urban residents living there that have the great-est effects.

Urban form and density131

Urban form and density are associated with a range of socialand environmental consequences. On the one hand, theextremely high densities of many cities in developingcountries – particularly in informal settlements and otherslums – result in increased health risks, and high levels ofvulnerability to climate change and extreme events. At theother extreme, the extremely low densities of many subur-ban areas in North America are associated with high levels ofhousehold energy consumption as a result of sprawlingbuildings and extensive car usage.

Urban sprawl refers to the increasing geographicalspread of urban areas into areas that were not previouslybuilt up.132 In many developing countries, the relatedprocess of peri-urbanization is increasingly taking place.133

These interfaces are affected by some of the most seriousproblems of urbanization, including intense pressures onresources, slum formation, lack of adequate services such aswater and sanitation, poor planning, and degradation offarmland. They are of particular significance in developingcountries, where planning regulations may be weak orweakly enforced, and result in areas with complex patternsof land tenure and land use.

At its simplest, urban density is measured by dividinga given population by its area. In the case of urban areas, thewidely varying definitions of the spatial extent of these areaslead to a great deal of difficulty in generating comparablestatistics for different towns and cities. Dividing the popula-tion of a metropolitan area by the administrative areacontained within its official boundaries is a highly unreliablemeasure – particularly for comparisons – because the densitywill vary according to the definition of these boundaries.134

In addition, standard measures of density are calculated overan entire land area, without taking into account the levels of

connectivity. In this regard, the gradual transformation of theurban form of Curitiba (Brazil) from a predominantly radial-circular form to a more linear pattern of development hasreduced the city’s overall density, yet has facilitated thedevelopment of a more rapid and effective public transporta-tion system and various other social and environmentalbenefits.135

In general and at a global level, there is strongevidence that urban densities have been declining over thepast two centuries.136 Perhaps the most detailed andcompelling assessment of this phenomenon is provided by aWorld Bank report that records the decline in the averagedensity of developed country cities from 3545 to 2835people per square kilometre between 1990 and 2000.During the same period, the average urban populationdensity in developing countries declined from 9560 to 8050people per square kilometre.137 The reduction in urbandensities is likely to continue into the future. It is estimatedthat the total population of cities in developing countries willdouble between 2000 and 2030; but their built-up areas willtriple from approximately 200,000 square kilometres toapproximately 600,000 square kilometres. During the sameperiod, the population of cities in developed countries isprojected to increase by approximately 20 per cent, whiletheir built-up areas will increase by 2.5 times: from approxi-mately 200,000 square kilometres to approximately 500,000square kilometres. These agglomerated figures for developedand developing countries conceal a great deal of regionalvariation (see Table 3.17). Southeast Asian cities were almostfour times as densely populated as European cities, andalmost eight times as densely populated as those in NorthAmerica and Australasia. When disaggregated by nationalincome levels, Table 3.17 shows that cities in low-incomecountries are more than four times as densely populated ascities in high-income countries.

In summary, spatially compact and mixed-use urbandevelopments have several benefits in terms of GHGemissions:

• Reduced costs for heating and cooling resulting fromsmaller homes and shared walls in multi-unit dwellings(see above).

• The use of energy systems covering a broader area (e.g.district) for cooling, heating and power generation, aswell as lesser line losses related to electricity transmis-sion and distribution. The use of micro-grids to meetlocal requirements of electricity can create efficienciesin storage and distribution.138

• Reduced average daily vehicle kilometres travelled infreight deliveries and by private motor vehicles percapita. Population density increases accessibility to suchdestinations as stores, employment centres andtheatres.139 It has been found that with all othervariables constant except density, a ‘household in aneighbourhood with 1000 fewer units per square miledrives almost 1200 miles more and consumes 65 moregallons of fuel per year’ over a household in a higherdensity neighbourhood.140


Region Persons per square kilometre1990 2000

Developed countries 3545 2835Europe 5270 4345Other developed countries 2790 2300

Developing countries 9560 8050East Asia and the Pacific 15,380 9350Latin America and the Caribbean 6955 6785Northern Africa 10,010 9250South and Central Asia 17,980 13,720Southeast Asia 25,360 16,495Sub-Saharan Africa 9470 6630Western Asia 6410 5820

High-income countries 3565 2855Upper-middle income countries 6370 5930Lower-middle income countries 12,245 8820Low-income countries 15,340 11,850

Source: adapted from Angel et al, 2005

Table 3.17

Average populationdensity of cities’ built-up areas

There is strongevidence that urbandensities have beendeclining over thepast two centuries

Spatially compactand mixed-use urbandevelopments haveseveral benefits interms of GHGemissions

n Urban density and greenhouse gasemissions

Urban form and urban spatial organization can have a widevariety of implications for a city’s GHG emissions. The highconcentrations of people and economic activities in urbanareas can lead to economies of scale, proximity and agglom-eration – all of which can have a positive impact upon energyuse and associated emissions, while the proximity of homesand businesses can encourage walking, cycling and the useof mass transport in place of private motor vehicles.141 Someresearchers suggest that each doubling of average neighbour-hood density is associated with a decrease of 20 to 40 percent in per-household vehicle use with a correspondingdecline in emissions.142 An influential paper published in1989 suggested that gasoline use per capita declines withurban density, although this relationship weakens once GDPper capita is brought into consideration.143 It has also beenargued that ‘by the middle of the century the combination ofgreen buildings and smart growth could deliver the deeperreductions that many believe are needed to mitigate climatechange’.144

A recent study of GHG emissions in Toronto (Canada)deals with the issue of density explicitly. The study depictsboth the overall patterns of GHG emissions and examineshow these vary spatially throughout the Toronto CensusMetropolitan Area: as the distance from the central coreincreases, private motor vehicle emissions begin to dominatethe total emissions.145 This pattern is supported by an earlierstudy, which found that low-density suburban developmentin Toronto is 2 to 2.5 times more energy and GHG intensivethan high-density urban core development on a per capitabasis.146

Density may also affect household energy consump-tion. More compact housing uses less energy for heating. Forexample, households in the US living in single-familydetached housing consume 35 per cent more energy forheating and 21 per cent more for cooling than comparablehouseholds in other forms of housing. In addition, denseurban areas generate a more intense urban heat-islandeffect147 that raises air temperature in a typical US city by1°C to 3°C over the surrounding rural area. This increasesthe number of ‘cooling days’ and decreases the number of‘heating days’, with the latter tending to have a greater effecton energy consumption. Consequently, residential buildingsin dense urban areas tend to consume lower levels ofenergy.148

Any assessment of changing density and changingemissions needs to take multiple factors into account. It isnecessary to assess the GHG emissions of different types ofurban development both between different cities and withinthe same city. While it appears that decreasing urban densitymay be implicated in increasing GHG emissions, the data areaffected by a variety of other variables, including overallincome levels. For example, cities in South Asia are not onlymore densely settled than cities in North America, but alsohave much lower GHG emissions. The difference in thelatter is due much more to income and consumptionpatterns than to variations in income levels. For example,London’s annual emissions declined from 45.1 to 44.3

million tonnes between 1990 and 2006, despite the popula-tion growing by 0.7 million people, the built-up areaincreasing from 1573 to 1855 square kilometres, and urbandensity decreasing from 6314 to 5405 persons per squarekilometre.149 In this particular situation, per capita GHGemissions appeared to decline at the same time as urbandensity declined. While it may appear that the decreaseddensity did not influence GHG emissions, in fact the declinein emissions can be attributed to the halving of industrialemissions, as industrial activity has relocated to other partsof the UK or overseas.

Dense urban settlements can therefore be seen toenable lifestyles that reduce per capita GHG emissionsthrough the concentration of services that reduces the needto travel large distances, the better provision of public trans-portation networks, and the constraints on the size ofresidential dwellings imposed by the scarcity and high cost ofland. Yet, conscious strategies to increase urban density mayor may not have a positive influence on GHG emissions andother environmental impacts. Many of the world’s mostdensely populated cities in South, Central and Southeast Asiasuffer severely from overcrowding, and reducing urbandensity will meet a great many broader social, environmentaland developmental needs. However, people do often wish tostay in the same location, and improvements can be achievedthrough upgrading. High urban densities can cause localizedclimatic effects, such as increased local temperatures.150 Inaddition, a variety of vulnerabilities to climate change are alsoexacerbated by density. Coastal location, exposure to theurban heat-island effect, high levels of outdoor and indoor airpollution, and poor sanitation are associated with areas ofhigh population density in developing country cities.151

However, these also provide clear opportunities for simulta-neously improving health and cutting GHG emissions throughpolicies related to transport systems, urban planning, buildingregulations and household energy supply.152

However, it should be noted that density is just one ofa variety of factors that influences the sustainability of urbanform. It has been argued that compactness alone is neither anecessary nor sufficient condition for sustainability,153 andat least seven design concepts for a sustainable urban formhave been identified – namely, compactness, sustainabletransport, density, mixed land uses, diversity, passive solardesign, and greening.154 Based on these criteria, the‘compact city’ model is identified as being most sustainable,followed by the ‘eco-city’, ‘neo-traditional development’ and‘urban containment’ – although this classification andranking is based on reviews of literature rather than empiri-cal research. A more complex relationship between land useand GHG emissions involves a model that also takes intoaccount landscape impacts (deforestation, carbon sequestra-tion by soils and plants, urban heat island), infrastructureimpacts, transportation-related emissions, waste manage-ment-related emissions, electric transmission and distrib-ution losses, and buildings (residential and commercial).There are complex relationships between these factors – forexample, denser residential areas may have lower levels ofcar use, but simultaneously present fewer options for carbonsequestration.155

The high concentrations ofpeople andeconomic activitiesin urban areas canlead to economies ofscale, proximity andagglomeration – allof which can have apositive impact uponenergy use andassociated emissions

Dense urban settle-ments … enablelifestyles that reduceper capita GHGemissions

Conscious strategiesto increase urbandensity may or maynot have a positiveinfluence on GHGemissions and otherenvironmentalimpacts


Although the relationship between urban density andGHG emissions is complex, there are certain directions thatcan be identified that are of relevance for urban policy.These do not amount to wholesale recommendations infavour of densification, but rather look at strategically assess-ing population distributions in a manner that contributes tobroader goals of climate change mitigation. Encouragingdensification at an aggregate level – for example, withinadministrative boundaries – risks neglecting the importantenvironmental and social roles played by gardens and openspaces. It is also worth considering the different housingneeds for individuals at different life stages, and reconsider-ing the notion of ‘housing for life’ that has been prevalent inmany national housing policies. In this regard, dense settle-ment patterns may meet the needs of certain groups withinsociety, but not others.

In general, density provides the potential for access toand greater use of public transport and of walking andcycling – where urban space is designed to meet the needsof users. A study of London shows a ‘positive link betweenhigher density areas and levels of public transport accessacross London, which is reflected in the decisions thatpeople make about how to get to work’.156 It furtherconcludes that ‘on balance, people will use public transportwhere it is available, especially in high density, centrallylocated areas’. People appear willing to ‘trade off’ morespace in their home for other qualities of a residential area,including personal and property safety, the upkeep of thearea, and proximity to shops and amenities.

Localized areas of relatively high densities arerequired to generate greater efficiencies in the usage ofpublic transportation; but this can be consistent withmeeting a variety of other demands from urban residents. Ofcourse, the precise form that these transportation networks– and other urban networks for supplying electricity, water,etc. – should take requires detailed local study. Overall,density is one of several factors that affects energy use (and,by extension, GHG emissions) from towns and cities.Addressing these issues requires ongoing analysis of urbanprocesses rather than simply taking a snapshot of urban format a particular moment in time.

The uses of land and spatial distribution of populationdensities within an urban area define its structure or form.Urban spatial structures play a major role in determining notonly population densities, but also the transportation mode(e.g. the relative importance of public versus private modes)and with it cities’ levels of energy use and GHG emissions.While urban structures do evolve with time, driven bychanges in the localization of economic activities, real estatedevelopments and population, their evolution is slow andcan seldom be shaped by design. The larger the city, the lessit is amenable to change its urban structure.

Four urban structures or forms can be distin-guished.157 In the first, mono-centric, represented by suchcities as New York (US), London (UK), Mumbai (India) andSingapore, most economic activities, jobs and amenities areconcentrated in the central business district (CBD). Hereauthorities should focus on promoting public transport asthe most convenient transport mode, for most commuters

travel from the suburbs to the CBD. In the second, poly-centric, exemplified by such cities as Huston (US), Atlanta(US) and Rio de Janeiro (Brazil), few jobs and amenities arelocated in the centre and most trips are from suburb tosuburb. A very large number of possible travel routes exists,but with few passengers per route. Therefore public trans-port is difficult and expensive to operate and individualmeans of transportation or collective taxis are and should bepromoted as the more convenient transportation options forusers. The third one, composite (or multiple-nuclei) model, isthe most common type of urban spatial structure containinga dominant centre together with a large number of jobslocated in the suburbs. Most trips from the suburbs to theCBD are made and should be promoted by public transport,while trips from suburb to suburb are made with individualcars, motorcycles, collective taxis or minibuses. The fourth,also called urban village model, does not exist in the realworld, but can be found only in urban master plans. In thismodel, urban areas contain many business centres,commuters travel only to the centre which is the closest totheir residence and have more opportunities to walk orbicycle to work. It is an ideal because it requires less trans-portation and roads, thus, in theory, dramatically reducingdistances travelled, energy used and, as a consequence,emissions of GHGs and other pollutants. However it is notfeasible, as ‘it implies a systematic fragmentation of labourmarkets which would be economically unsustainable in thereal world’.158

The urban economy

The types of economic activities that take place within urbanareas also influence GHG emissions. Extractive activities(such as mining and lumbering) and energy-intensivemanufacturing are obviously associated with higher levels ofemissions – especially when the energy for these is suppliedfrom fossil fuels. However, there are fewer of these activitiesin many cities in developed countries, as lower transporta-tion costs and the lower cost of labour elsewhere haveencouraged industries to relocate elsewhere. In London, forexample, industrial emissions halved between 1990 and2006, as industrial activity has relocated to other parts of theUK or overseas.159

Yet, all urban areas rely on a wide range of manufac-tured goods (produced within the urban area or elsewhere),and manufacturing areas similarly rely on the servicesprovided by certain urban centres. This relationship can existwithin countries. In South Africa (and as noted above), theindustrial town of Sedibeng (population of 880,000 andannual per capita emissions of 28.6 tonnes CO2eq) is linkedwith the services provided by the City of Johannesburg(population 3.6 million and annual per capita emissions of 5.6tonnes CO2eq) (see Table 3.13). As described above, thisprocess exists across national boundaries with many of theworld’s cities acting as centres for the trading of commoditiesand consumption of manufactured goods, while generatingfew emissions from within their own boundaries. With this inmind, the next section examines alternative approaches onhow to measure the emissions from urban areas.

In general, densityprovides the poten-tial for access to andgreater use of publictransport and ofwalking and cycling

Urban spatial structures play amajor role in determining … thetransportation mode… and with it cities’levels of energy useand GHG emissions.

The types ofeconomic activitiesthat take placewithin urban areas… influence GHGemissions


The influence of the urban economy on patterns ofemissions can be seen in the large variations in the propor-tion of a city’s GHG emissions that can be attributed to theindustrial sector.160 Industrial activities in many rapidlyindustrializing developing countries (such as China) areresponsible for a large proportion of urban GHG emissions.Indeed, while 12 per cent of Chinese emissions were due tothe production of exports in 1987, this figure had increasedto 21 per cent in 2002 and 33 per cent (equivalent to 6 percent of total global CO2 emissions) in 2005.161 A recentpaper on this issue describes the situation as follows:

… many of the countries in the western worldhave dodged their own carbon dioxideemissions by exporting their manufacturing to… China. Next time you buy something with‘Made in China’ stamped on it, ask yourself whowas responsible for the emissions that createdit.162

In contrast, GHG emissions from the industrial sector incities elsewhere are much lower, generally reflecting atransition to service-based urban economies. Industrial activ-ities account for just 0.04 per cent in Washington, DC (US)(largely because of the narrow spatial definition of theDistrict of Columbia); 7 per cent in London (UK); 9.7 percent in São Paulo (Brazil); and 10 per cent in Tokyo (Japan)and New York City (compared to 29 per cent for the US as awhole). The declining importance of industry in causingemissions is evident in several cities. In Rio de Janeiro, theindustrial sector’s proportion of emissions declined from 12per cent in 1990 to 6.2 per cent in 1998; and in Tokyo, itdeclined from 30 to 10 per cent during the last threedecades.163

The politics of measuring emissions

There are striking differences in the contribution of differenturban areas to climate change. Measured purely in terms ofdirect emissions per person from a given urban area, thesemay vary by a factor of 100 or more. As noted earlier in thischapter, different ‘scopes’ of emissions may be taken intoaccount164 (see Tables 3.2 and 3.4). In practice, GHGemission inventories from urban areas that include Scope 3emissions are very rare. And the extent to which theseScope 3 emissions (i.e. indirect or embodied emissions) areincluded is very arbitrary and there is no agreement as to acomparable framework to compare emissions of this typebetween urban areas. If Scope 3 or embodied emissions areincluded, it is likely that the per capita emission of GHGsallocated to a city will increase significantly – particularly ifthe city is large, well-developed and with a predominance ofservice and commercial activities.165 In addition, it is almostimpossible to compile a comprehensive inventory of Scope 3emissions that takes into account all the consumption of theindividuals living in an urban area. In other words, ‘emissionscan be attributed either to the spatial location of actual releaseor to the spatial location that generated activity that led to theactual release’.166 A detailed Scope 3 inventory should also

subtract the embodied energy in goods made in that city andsubsequently exported.

The data presented in this chapter show that urbanareas with a heavy concentration of industrial and manufac-turing activities have high levels of GHG emissions. Theyalso show that wealthier urban areas have high emissions –although these may be lower than non-urban but equallywealthy areas. The per capita emissions of GHGs by individu-als including those caused by the goods they consume andwastes they generate vary by a factor of more than 1000depending on the circumstances into which they were bornand their life chances and personal choices. Obviously, theirlifetime contribution is also influenced by how long theylive. Poorer groups with low annual per capita emissionsoften have life expectancies of 20 to 40 years less than high-income groups. Unsustainable levels of consumption,which drive the processes of production, are thereforecrucial to understanding the contribution of urban areas toclimate change. This section thus discusses alternativeapproaches on how to calculate the contribution of urbanareas to climate change, thereby helping to provide a frame-work for understanding and addressing the root causes ofGHG emissions.

As noted above, urban areas in different countries,and even within the same country, have different emissionsprofiles according to environmental, economic, social, politi-cal and legal differences over space and across nationalboundaries. This influences the balance of production andconsumption of GHGs, as many of the most highly emittingactivities have been displaced to rapidly industrializing devel-oping countries. The Kyoto Protocol – and its likely successortreaty – also creates incentives for developed countries167 toreduce the emissions from within their national boundaries,which may create perverse incentives for raised levels ofemissions in developing countries which are not subject tothese constraints. However, the principle of ‘common butdifferentiated responsibilities’168 adopted in the negotiationsought to prevent this from happening. Similarly, as theconcept of ‘nationally appropriate mitigation actions’169

becomes adopted at the local level, positive incentives maybe created to encourage urban areas to reduce theiremissions in contextually appropriate ways.

In particular, political forces and the policy environ-ment – at the global, national and local levels – can be astrong underlying factor in shaping GHG emissions. At theglobal level, the establishment of national targets for devel-oping countries170 is an important factor driving reductionsin emissions. The implementation of CDM projects – inwhich emissions reductions in developing countries aresupported by developed country actors – can also shapeemissions patterns. Where local and national governments in developing countries support CDM activities,171 this canhave a substantial local impact upon local emissions. At the same time, local governments can shape city emissionsthrough several different pathways: through undertakingemissions reductions activities in their own activities (e.g.local authority buildings and vehicle fleets); through chang-ing the legislative environment (e.g. through increasedtaxation on highly polluting industries or tax incentives

Industrial activitiesin many rapidlyindustrializingdeveloping countries(such as China) areresponsible for alarge proportion ofurban GHGemissions

In contrast, GHGemissions from theindustrial sector incities elsewhere aremuch lower, gener-ally reflecting atransition to service-based urbaneconomies

The per capitaemissions of GHGsby individuals …vary by a factor ofmore than 1000depending on thecircumstances intowhich they wereborn and their lifechances andpersonal choices

Political forces andthe policy environ-ment … can be astrong underlyingfactor in shapingGHG emissions


encouraging the use of low-carbon technology); and throughencouraging behavioural change among citizens (e.g.through mass awareness or educational programmes).172

n Ecological footprints versus carbon footprints

One useful approach for calculating GHG emissions fromurban areas is to consider ecological footprints. The ecologi-cal footprint is a concept that measures the area of theEarth’s surface required to provide the consumption needsof an individual, urban area or country. The concept of theecological footprint recognizes that larger areas of land arerequired to sustain life inside urban areas than are containedwithin municipal boundaries of the built-up area – with thisarea being much larger for wealthy cities.173 Most cities andregions depend on resources and ecological services –including food, water and the absorption of pollutants – fromoutside their boundaries; many depend on those fromdistant ecosystems; and the environmental consequences ofurban activities are thus felt globally or in distant regions.Ecological footprint analysis has been used in recent years todevelop a related concept: the carbon footprint (see Box1.1). A full carbon footprint therefore takes into account allthe emissions included in ‘Scope 1’, ‘Scope 2’ and ‘Scope 3’,but places a greater emphasis on the indirect emissions fromproducts and services that are consumed but not directlycontrolled.

Although often used interchangeably, the implicationsof an emissions inventory and a carbon footprint can there-fore be quite different. The emissions inventory is derivedfrom the UNFCCC model of national inventories thataccounts for GHG emissions produced within a geographi-cally defined boundary. In contrast, the carbon footprint isderived from the concept of the ecological footprint, and isfocused on the GHG emissions associated with the consump-tion of goods and services. The origin of GHG emissions istherefore better understood through the use of consump-tion-based assessments. In relation to ecological footprints,it has been concluded that ‘wealthy nations appropriatemore than their fair share of the planet’s carrying capac-ity’.174 Similarly, the use of a consumption-based analysis ofemissions, derived from a carbon footprint approach, willhelp to make it clearer which countries, urban areas andindividuals are responsible for more than their fair contribu-tion to global climate change.

n Production-based versus consumption-based approaches

The use of a production-based approach to assessing thecontribution of urban areas to GHG emissions can lead toperverse and negative effects. Urban areas will be able toreduce their emissions through creating disincentives fordirty economic activities that generate high levels of GHGs(e.g. heavy industry), and incentives for clean economicactivities that generate much smaller emissions (e.g. high-tech industries). This situation can already be seen: manypolluting and carbon-intensive manufacturing processes areno longer located in Europe or North America, but have beensited elsewhere in the world to take advantage of lower

labour costs and less rigorous environmental enforcement.Since developing countries are not required to reduceemissions under the UNFCCC, a process of ‘carbon leakage’can take place, where emissions are moved rather thanreduced.175 Yet, climate change is a global phenomenon:emissions of a given quantity of CO2 have the same effect onthe global climate wherever in the world these are released.From the perspective of global climate change, the conse-quences are the same irrespective of whether an industry islocated within the urban areas or rural areas of a developedor a developing country. The underlying drivers for theseemissions are the demands of consumers who desire particu-lar products. Thus, an assessment of the contribution ofurban areas to climate change needs to reflect the location ofthe people making these demands.

At a national level, input–output analyses have beenused to show national average per capita carbon footprints.These take into account construction, shelter, food, clothing,mobility, manufactured products, services and trade.National average per capita footprints vary from approxi-mately 1 tonne CO2eq in many African countries toapproximately 30 tonnes CO2eq in Luxembourg and the US.The proportion of these emissions attributed to internalconsumption varies greatly: with low figures in small city-states and countries with low levels of imports (e.g. 17 percent in Hong Kong and 36 per cent in Singapore) and highfigures in major industrial and manufacturing countries (e.g.94 per cent in China and 95 per cent in India) and incountries with low levels of imports as a result of poverty(e.g. 90 per cent in Madagascar and Tanzania).176 Thismethod for measuring responsibility shows clearly that thecountries with high levels of consumption and imports areresponsible for much greater volumes of GHG emissionsthan a production-based approach would indicate.

The use of a production-based system to assess thecontribution of urban areas to climate change diverts atten-tion and blame from the high-consumption lifestyles thatdrive unsustainable levels of GHG emissions. This systemfails to identify the areas in which interventions are requiredto reduce emissions by focusing attention on only one part ofmultiple complex commodity chains. In addition, analysingemissions at a city level generates a variety of logisticalproblems. For instance, there are large information gaps(particularly in developing countries); different informationis available at different geographic levels; and politicalboundaries of cities may change over time and often includeboth rural and urban populations (as is the case for Beijingand Shanghai in China).177

Production-based emissions methodologies thereforedistort the responsibility of different cities for generatingGHGs. Different types of cities will be affected in differentways by this approach: ‘in service-oriented cities, consump-tion-related emissions are more important than thoseproduced by production’.178 Consequently, the responsibilityof successful production-oriented centres such as Beijingand Shanghai is exaggerated, while that of wealthy service-oriented cities including many cities in North America andEurope is underemphasized. The fact that Beijing andShanghai have per capita emissions of more than twice the

The use of aconsumption-basedanalysis of emissions… will help to makeit clearer whichcountries, urbanareas and individuals areresponsible for more than their fair contribution toglobal climatechange

From the perspective of globalclimate change, theconsequences arethe same irrespective ofwhether an industryis located within theurban areas or ruralareas of a developedor a developingcountry

Production-basedemissions method-ologies … distort theresponsibility ofdifferent cities forgenerating GHGs


Chinese average therefore reflects not only the relative afflu-ence of these cities (and the spatially uneven incorporationof different parts of China into global economic networks),but also the role that they play in manufacturing consumerproducts that are used elsewhere in China and throughoutthe world.

In contrast, a consumption-based approach attemptsto address the origin of emissions in a more comprehensivemanner. This type of accounting system would result in alower level of GHG emissions to developing countries (witha likely substantial reduction in the GHG emissions allocatedto China and Chinese cities), and should – in theory – influ-ence consumers in developed countries to assumeresponsibility for choosing the best strategies and policies toreduce emissions.179 Consumption-based mechanisms inher-ently have greater degrees of uncertainty (as there are manymore systems to be incorporated in the final calculation); butthey do provide considerable insight into climate policy andmitigation, and should probably be used at least as a comple-mentary indicator to help analyse and inform climatepolicy.180 They respond to broader concerns about sustain-ability by ensuring that as well as improving environmentalperformance within city boundaries, there is a reduction inthe transfer of environmental costs to other people, distantplaces or future times.181

A consumption-based approach can also be bench-marked against global needs to limit GHG emissions toprevent dangerous climate change. The best availableestimates suggest that annual global GHG emissions need tobe reduced from approximately 50 billion tonnes to 20billion tonnes CO2eq per year by 2050. With an estimatedglobal population of 9 billion in 2050, this means thatindividual carbon footprints around the world will have to beat an average of less than 2.2 tonnes per year. In particular, itmust be recognized that different locations have access todifferent sources of energy: and a fair allocation of emissionsshould not mean that individuals or urban areas located ingeographical proximity to abundant geothermal or hydroelec-tric sources of energy are able to cash in these spatialadvantages to produce greater emissions from other activi-ties. Climate change is, indeed, a global challenge, and needsto be addressed with global solutions.

Recent research has highlighted the role of urban foodconsumption in generating GHG emissions. The processesinvolved in the production and distribution of food for urbanconsumption use significant amounts of energy and alsogenerate substantial GHG emissions. Fruits and vegetablesconsumed in developed countries often travel between2500km and 4000km from farm to store.182 In NorthAmerica, for example, the average food product in the super-market has travelled 2100km before ending up on a shelfand the food system accounts for some 15 to 20 per cent ofthe energy consumption in the US.183 Research has alsoshown that a basic diet composed of imported ingredientscan use four times the energy and produce four times theGHG emission than an equivalent diet with local ingredients.The potential for localized urban food production andconsumption in promoting energy efficiency and reducingGHG emissions is clear.

However, this needs to be seen alongside the develop-ment benefits that the export of agricultural products canbring to developing countries. Air-freighted products arefrequently seen as major problems in the emission of GHGs;yet the issues are much more complex. In the UK, freshproduce air-freighted from Africa is responsible for less than0.1 per cent of national emissions – and the emissions fromsub-Saharan African countries are minuscule in the firstplace. At the same time, more than 1 million African liveli-hoods are supported by growing this produce.184 In addition,some agricultural practices that reduce ‘food kilometres’ –such as using greenhouses to grow tropical crops in temper-ate latitudes – can have a larger impact upon emissions thanthe distance travelled.

Distinct challenges are associated with consumption-based approaches to measuring the contribution ofindividuals and urban areas to climate change; yet these canprovide considerable insights into climate policy and mitiga-tion.185 In practice, both production- and consumption-basedapproaches will continue to be required. Table 3.18 shows the main driving forces for GHG emissions from bothperspectives. In many sectors – particularly in energy, transport, and residential and commercial buildings – inter-ventions to address production-related emissions are similarto those addressing consumption-related emissions. In termsof industry, however, a consumption-based approach placesan added emphasis on the global dimensions of emissions –spreading the net wider in terms of where the impacts ofindividual activities are actually felt. Addressing emissionsfrom a consumption-based approach is therefore much moreabout reducing emissions rather than merely shifting themelsewhere.

Consumption-based approaches help to ensure thatthe allocation of responsibility for GHG emissions simultane-ously addresses concerns of climate, environmental andgender justice. Of course, global action is required to reducethe risks of climate change – yet the burden for meeting thisgoal should not fall on individuals or urban areas that havelittle responsibility for it.186 Rather, a consumption-basedanalysis ensures that the responsibility for addressing thisproblem lies with the individuals, urban areas and countrieswho have the greatest responsibility for causing it. Similarly,production-based inventories mask the gendered nature ofindividual energy-use patterns.187 Indeed, one studysuggests that more men than women own cars in Sweden,and concludes that ‘if women’s consumption levels were tobe the norm, both emissions and climate change would besignificantly less than today’.188

n Individual versus urban drivers of emissionsThe preceding discussion makes it clear that consumption isperhaps the most important driver of GHG emissions. In thisregard, individuals can be seen as the basic unit affectingemissions. It is the consumption choices and behaviour ofindividuals that ultimately lead to the use of energy and theproduction of GHGs. However, it needs to be stressed thatthe choices that individuals make are shaped by structuralforces in the areas in which they live. For example, individu-als living in urban areas with effective integrated public

Consumption-basedmechanisms …respond to broaderconcerns aboutsustainability byensuring that …there is a reductionin the transfer ofenvironmental coststo other people,distant places orfuture times

Climate change is …a global challenge,and needs to beaddressed withglobal solutions

Consumption-basedapproaches help toensure that theallocation of responsibility forGHG emissionssimultaneouslyaddresses concernsof climate, environmental andgender justice


High levels ofwealth and disposable incomelead to generallyhigh levels ofconsumption and,hence, GHGemissions

Women tend tocontribute less toclimate change as anoutcome ofconsumptionpatterns, social roles and pro-environmentalbehaviour

transportation systems or safe, well-maintained bicyclepathways will be much more able to reduce distancestravelled by car. As an increasing proportion of the world’spopulation lives in urban areas, the choices that are made inrelation to investments in urban infrastructure will have agrowing role in determining future GHG emissions.

In developed countries, high levels of wealth anddisposable income lead to generally high levels of consump-tion and, hence, GHG emissions, as is evident from some ofthe national inventories discussed earlier in this chapter.189

As was also discussed, the economies of scale and the advan-tages of density mean that urban residents in these countriestend to generate fewer GHG emissions than the nationalaverage – at least from a production perspective. Individualdrivers of emissions in urban areas in developed countriesare still – obviously – related to personal consumptionhabits. Yet, at the same time, the consumption patterns ofwealthy residents in developing countries also drive upnational GHG emissions. It should also be noted that indeveloping countries, average incomes in urban areas areoften substantially higher than in rural areas. Individuals andhouseholds with higher incomes – and greater consumption– are therefore likely to be concentrated in these urbanareas.

The behaviour of urban residents is shaped by culturaland social contexts. These factors can drive individualchoices that affect emissions, including the choice of car,decisions about transportation modes and the ways in whichenergy is used at home (switching off lights, managingheating and cooling), all of which can make a difference to

urban emissions.190 More broadly, the values placed onleading more self-sufficient lives can affect a wide range ofconsumption decisions and, therefore, emissions generation.

These contexts include gender roles and expecta-tions. On average, women tend to contribute less to climatechange as an outcome of consumption patterns, social rolesand pro-environmental behaviour.191 In general, peopleliving in poverty tend to contribute less to climate change,and more women than men in almost all societies live inpoverty. Prescribed gender roles mean that women tend toparticipate in different activities than men, and frequentlytravel less for business purposes. In addition, there isevidence that women in developed countries are more likelyto consider the environmental impact of purchasingdecisions. However, this analysis needs to be tempered bythe fact that for various activities – particularly householdservices such as heating and food preparation – it is impossi-ble to disaggregate the relative contribution of differentmembers within the same household. Yet, despite theirlower contribution to climate change, women are more likelyto be affected by its impacts.192

However, these individual choices need to be seen inthe context of the provision (or lack) of particular forms ofinfrastructure that can lead to marked differences in urbanemissions. The same per capita electricity consumption cangive widely diverging per capita GHG emissions based on theenergy pathways adopted at the urban and national level.Among the factors leading to Tokyo’s lower emissions thanthose in Beijing and Shanghai are its efficient urban infra-structure, greater reliance on lower-emitting sources of


Sector What drives growing GHG emissions in urban areas?Production perspective Consumption perspective

Energy supply: A large proportion comes from fossil fuel power GHGs from energy supply now assigned to consumers of energy stations – hence, a growth in electricity provision supplies/electricity, so growth in GHG emissions is driven by increasing from high GHG-emitting sources. Many large fossil energy use; consumers are also allocated the GHGs from the energy used fuel power stations are located outside urban areas; to make and deliver the goods and services that they consume.but the GHG emissions from the electricity used in urban areas are usually allocated to these urban areas.

Industry: Growing levels of production; growing energy intensity GHGs from industries and from producing the material inputs that they in what is produced; importance of industries producing draw on no longer allocated to the enterprises that produce them, but goods whose fabrication entails large GHG emissions rather to the final consumers of the products, so again GHG growth driven (e.g. motor vehicles). by increased consumption.

Forestry and Many urban centres have considerable agricultural GHGs from these no longer allocated to rural areas (where they are agriculture: output and/or forested areas, but mostly because of produced), but rather to the consumers of their products (many or most in

extended boundaries that encompass rural areas; from urban areas); note how energy intensive most commercial agriculture has the production perspective, GHGs generated by become; also the high GHG implications for preferred diets among deforestation and agriculture are assigned to rural areas. high-income groups (including imported goods, high meat consumption,

etc.).Transport: Growing use of private motor vehicles; increases in As in the production perspective; GHG emissions from fuel use by people

average fuel consumption of private motor vehicles; travelling outside the urban area they live in are allocated to them (thus, increased air travel (although this may not be allocated includes air travel); also concern for GHG emissions arising from investment to urban areas). in transport infrastructure.

Residential/ Growth in the use of fossil fuels and/or growth in As in the production perspective, but with the addition of GHG emissions commercial electricity use from fossil fuels for space heating and/or arising from construction and building maintenance (including the materials buildings: cooling, lighting and domestic appliances. used to do so).Waste and Growing volumes of solid and liquid wastes and of Large and often growing volumes of solid and liquid wastes with GHGs; wastewater: more energy-intensive waste. these are allocated to the consumers who generated the waste, not to the

waste or waste dump.Public sector N/A Conventional focus of urban governments on attracting new investment, and governance: allowing urban sprawl and heavy investment in roads, with little concern for

promoting energy efficiency and low GHG emissions.

Notes: For a discussion of mitigation action based on these two perspectives, see Table 5.11. N/A = not available.

Source: based on Satterthwaite, 2009, pp548–549

Table 3.18

Urban GHG emissions:Production versusconsumption perspectives

energy generation, and more efficient end-use technology, aswell as the different types of industrial activities takingplace.193 Independently of the level of affluence, a well-managed city with a good public transportation system,whose population has access to water and sanitation, toadequate health services and to a good quality of life, is likelyto have fewer problems in dealing with a wide range ofenvironmental challenges – including climate change – thana city that is poorly managed.

Most US cities have three to five times the gasolineuse per person of most European cities; yet it is difficult tosee that Detroit has five times the quality of life ofCopenhagen or Amsterdam. Indeed, wealthy, prosperousand desirable cities can have relatively low levels of fuelconsumption per person.194 Most European cities have high-density centres where walking and bicycling are efficient andpleasant modes of transport and public transportation isoften well-planned and effective. In this regard, well-plannedand well-governed cities are central to delinking high livingstandards and high quality of life from high consumption andhigh GHG emissions.195

However, it should be remembered that cities andtowns also contain areas that have high concentrations ofpoverty and vulnerability, and many residents of these areaswill have extremely low emissions. For low-income house-holds in most developing countries, recent demographic andhealth surveys show that fuel use is still dominated bycharcoal, firewood or organic waste. Where access to this iscommercialized – as is the case in many urban centres – totalfuel use among low-income residents will be low because ofits high cost. If urban households are so constrained in theirincome levels that families can afford only one meal a day,their consumption will be generating only minisculeamounts of GHGs. Moreover, low-income urban householdsuse transport modes (walking, bicycling or public transporta-tion) with no or low emissions – most of which is used tomore than full capacity.196

CONCLUDING REMARKSAND LESSONS FOR POLICYActivities taking place in urban areas – including the actionsof individual urban residents – generate a range of GHGsthat contribute to climate change. Assessing the contribu-tion of cities to climate change is an important step indeveloping locally appropriate mitigation actions. The recentlaunch of a standard methodology that can be used by urbanareas around the world to produce comparable data is animportant component of this. Yet, as has been shown in thischapter, assessing the contribution of cities to climatechange is not a straightforward process, and there has beensubstantial debate about the proportion of global emissionsthat can or should be attributed to urban areas. This analysisleads to several key messages: the need for a better under-standing of the nature of emissions from cities; theconsiderable differences in GHG emissions between citiesand the wide range of factors contributing to this; thesubstantial differences in responsibility for GHG emissions

from different groups of people within cities; and the impor-tance of examining the underlying drivers of emissions.

There has been an increasing debate about theproportion of global emissions that can or should be attrib-uted to urban areas. This is partially due to the absence of astandardized methodology that has been globally agreed asrepresenting the emissions for which a city is ‘responsible’.But it is also compounded by variations in the definition of‘urban areas’ between different countries, the ways in whichurban boundaries are defined, and the quality of data avail-able. The main sectors for which emissions can be assessed –energy for electricity, transportation, commercial andresidential buildings, industry, waste, agriculture, land-usechange and forestry – are all relevant to urban areas, whichrely on goods, services and processes taking place bothinside and outside their boundaries.

There are large differences in GHG emissionsbetween countries and cities around the world, with percapita emissions varying by a factor of 100 or more betweenthe lowest- and highest-emitting countries. There are avariety of factors influencing the total and per capitaemissions of a city, including geographic situation (whichinfluences the amount of energy required for heating andlighting), demographic situation (related to both totalpopulation and household size), urban form and density(sprawling cities tend to have higher per capita emissionsthan more compact ones), and the urban economy (the typesof activities that take place, and whether these emit largequantities of GHGs).

However, there are more fundamental underlyingfactors affecting emissions, primarily related to the wealthand consumption patterns of urban residents. If consump-tion is taken into account, the emissions from wealthy citiesincrease substantially, while those from manufacturing citiesin developing countries decline. A consumption-basedapproach has substantial value when considering globalemissions reductions – as it removes the incentive simply to‘move’ the location of production to countries that are notbound by specific carbon emissions reduction targets. Theseunderlying drivers are inevitably complex, contextuallyspecific, and contingent on a wide range of structural, social,economic and political variables. Reducing urban emissionsrequires recognizing this complexity and addressing itaccordingly.197

In turn, these key findings generate several messagesfor policy at the global, national and local levels. The impor-tance of cities in directly and indirectly generating GHGemissions indicates that there should be a more central rolefor sub-national and urban governments in global responsesto climate change. Several global networks of cities havebeen formed with the intention of reducing GHG emissions,sharing knowledge and engaging in advocacy within theUNFCCC. However, there are limited pathways for cities toengage directly in global climate change policy or to receivefinancing for mitigation activities. Addressing this willrequire changes in both global and national policy, asnational governments will need to recognize the need forcities to act in this arena and provide appropriate legislativeframeworks.

Most US cities havethree to five timesthe gasoline use perperson of mostEuropean cities; yetit is difficult to seethat Detroit has fivetimes the quality oflife of Copenhagenor Amsterdam

The importance ofcities in directly andindirectly generatingGHG emissionsindicates that thereshould be a morecentral role for sub-national andurban governmentsin global responsesto climate change


The assessment of the contribution of cities toclimate change provided in this chapter also highlights someof the most important areas for responses by city authorities.First, it has been shown that activities undertaken directly bycities can be substantial producers of GHGs. City authoritiesare often responsible for operating large fleets of vehicles,large numbers of buildings and facilities such as wastedisposal sites. These can all produce large amounts of GHGs,yet can also be modified to reduce their contributions.

Second, urban form and the urban economy havebeen shown to be key factors influencing emissions at thecity level. Through their responsibilities for land-useplanning and attracting investment, city authorities can helpto shape the policy environment within which a range ofother stakeholders act. Encouraging relatively dense urbansettlements can reduce distances travelled by urbanresidents and can make public transportation a more appeal-ing prospect. A combination of regulations (e.g. in relation tocommercial and industrial energy standards) and incentives

(e.g. to support buildings with ‘green roofs’ or passive solarheating) can help to encourage businesses in cities tooperate in a way that reduces their contribution to climatechange.

Finally, local levels of government are appropriatelypositioned to engage directly with citizens to shape behav-iour. This chapter shows the importance of individualconsumption patterns in contributing to GHG emissionsfrom both within and outside city boundaries. City authori-ties and civil society can help to generate awareness of theimplications of consumption decisions, and can encourageindividual urban residents to act in a less carbon-intensivemanner. Addressing the challenge of climate change in citieswill require citizens, civil society, the private sector, localand national governments, and international organizations towork together in partnerships. Local authorities are locatedat a crucial nexus for engaging with these different groupsand playing a leading role in reducing the contribution ofcities to climate change.

1 UNFCCC, Article 3. See alsoChapter 2.

2 A brief overview of suchnetworks is provided inChapter 2.

3 UNEP et al, 2010.4 For a discussion of the charac-

teristics of the main GHGs, seeChapter 1.

5 UNFCCC, 2004.6 IPCC, 2006.7 Dodman, 2009.8 See the section on ‘Factors

influencing emissions’.9 WRI/WBCSD, undated. The

procedures of this protocolhave been adopted by a widerange of private-sector compa-nies (for more details, seewww.ghgprotocol.org).

10 Scope 1 emissions representdirect emissions from within agiven geographical area; Scope2 emissions are those associ-ated with electricity, heatingand cooling; and Scope 3emissions include those thatare indirect or embodied.

11 See also http://webapps01.un.org/dsd/partnerships/public/partnerships/1670.html.

12 ICLEI, 2008.13 Fugitive emissions are ‘inten-

tional or unintentional releaseof … [GHGs, which] mayoccur during the extraction,processing and delivery offossil fuels to the point of finaluse’ (IPCC, 2006, p4.6).

14 As discussed below in thesection on ‘The scale of urbanemissions’.

15 See note 10.16 As discussed below in the

section on ‘The politics ofmeasuring emissions’.

17 These are discussed in moredetail below in the section on

‘The politics of measuringemissions’.

18 Any new baseline inventory islikely to include aspects ofboth WRI/WBCSD’sCorporate Accounting andReporting Standard and ICLEI’sInternational LocalGovernment GHG EmissionsAnalysis Protocol. This willthus take into account thedirect emissions from a city, aswell as a selected componentof cross-boundary emissionsincluded within theWRI/WBCSD concepts ofScope 2 and Scope 3 (Kennedyet al, 2009a).

19 UNEP et al, 2010.20 Kates et al, 1998.21 Forstall et al, 2009.22 Satterthwaite, 2007.23 Parshall et al, 2009, 2010.24 These issues are discussed

further in the sections belowon ‘The scale of urbanemissions’ and ‘Factors influ-encing emissions’.

25 IEA, 2010, p35.26 IEA, 2010, pp24–25.27 IPCC, 2007e.28 Sims et al, 2007.29 Kennedy et al, 2009b.30 World Nuclear Association,

2010.31 Sustainable Energy Africa,

2006.32 Dhakal, 2009.33 Sims et al, 2007.34 Nuclear power plants have

very large levels of embeddedenergy in the building materialsand plant construction anddecommissioning, as well as inthe processing and storing ofradioactive waste – much ofwhich comes from fossil fuels.

35 Although this may, in part, be

changing now – at least insome countries – in responseto the need to reduce thedependence of electricitygeneration on fossil fuels inlight of the increasing concernover climate change.

36 These issues are discussed inmore detail in Chapter 5.

37 Sustainable Energy Africa,2006.

38 Satterthwaite and Sverdlik(2009), citing data from Legroset al (2009).

39 This section draws extensivelyon Dodman (2009).

40 Barker et al, 2007.41 Parshall et al, 2009.42 Romero Lankao et al, 2009a.43 Ewing et al, 2008.44 Johnsson-Latham, 2007.45 Compiled from data presented

in Newman (2006) andDodman (2009).

46 Darido et al, 2009.47 Compiled from data presented


48 Ewing et al, 2008.49 Ewing et al, 2008.50 Kutzbach, 2009.51 Takeuchi et al, 2007.52 Wright and Fulton, 2005, Figure

1.53 Wright and Fulton, 2005.54 Unpublished document, Dar es

Salaam City Corporation.55 WHO, 2004. See also UN-

Habitat 2007, Chapter 9.56 Woodcock et al, 2007.57 Bloomberg and Aggarwala,

2008.58 Kahn Ribeiro et al, 2007.59 Kahn Ribeiro et al, 2007.60 Kahn Ribeiro et al, 2007.61 Mayor of London, 2007.62 City of New York, 2009.63 Barker et al, 2007.

64 Kennedy et al, 2009b.65 Parshall et al, 2009.66 Ewing et al, 2008.67 Markham, 2009.68 Gupta and Chandiwala, 2009,

p4. The rest of the emissionswere from transport (33 percent), industrial processes (22per cent) and agriculture (1per cent).

69 Gupta and Chandiwala, 2009.70 Yuping, 2009.71 Sykes, 2009.72 See www.statcompiler.com, last

accessed 12 October 2010.73 Gupta and Chandiwala, 2009,

p11.74 Gupta and Chandiwala, 2009,

p11.75 This section draws extensively

on Dodman, 2009.76 Bai, 200777 Kennedy et al, 2009b.78 Sustainable Energy Africa,

2006.79 Dhakal, 2009.80 Ru et al, 2009.81 Barker et al, 2007.82 See Chapter 2.83 Kennedy et al, 2009b.84 Dodman, 2009.85 See below in the section on

‘The urban economy’.86 Hardoy et al, 2001.87 See section below on ‘Factors

influencing emissions’.88 Rogner et al, 2007.89 UN, undated.90 Satterthwaite, 2009.91 Harvey, 1993.92 VandeWeghe and Kennedy,

2007.93 That is, including counties

such as Arlington andAlexandria which are locatedin the neighbouring state ofVirginia.

94 City of New York, 2009.


NOTES

A combination ofregulations … andincentives … canhelp to encouragebusinesses in citiesto operate in a waythat reduces theircontribution toclimate change

Addressing thechallenge of climatechange in cities willrequire citizens,civil society, theprivate sector, localand national governments, andinternational organizations towork together inpartnerships

95 United States Department ofEnergy, 2008.

96 City of New York, 2009.97 City of New York, 2007.98 City of New York, 2007.99 City of New York, 2009.100 City of New York, 2009.101 Heede, 2006.102 Brown et al, 2008.103 Mayor of London, 2007.104 Baldasano et al, 1999.105 Gomes et al, 2008.106 See Table 1.4.107 The term ‘nationally appropri-

ate mitigation actions’ was firstused in the Bali Action Plan,the main outcome of COP-13,and recognizes that differentcountries may take differentnationally appropriate actionon the basis of equity and inaccordance with the principleof ‘common but differentiatedresponsibilities and respectivecapabilities’ (see Chapter 2).

108 Patricia Romero Lankao, perscomm., 2009.

109 Sustainable Energy Africa,2006, p83.

110 PADECO, 2009a.111 Ananthapadmanabhan et al,

2007. The two categories referto the 10 million people (1 percent of the population) in Indiawho earn more than 30,000rupees (approximatelyUS$700) per month, and the432 million people (38 percent of the population) whoearn less than 3000 rupees(approximately US$23) permonth.

112 Satterthwaite, 2009.113 PADECO, 2009b.

114 Wang and Huang, 1999.115 Roy, 2009.116 Satterthwaite, 2008a.117 Walraven, 2009.118 OECD, 1995.119 Walraven, 2009.120 See the section on ‘The politics

of measuring emissions’.121 See the section on ‘The

sources of greenhouse gasemissions’.

122 Valor et al, 2001.123 Glaeser and Kahn, 2008.124 Energy Information

Administration, undated.125 REN21, 2009.126 Romero Lankao et al, 2009a.127 Dalton et al, 2008.128 Jiang and Hardee, 2009.129 Martine, 2009.130 Newman, 2006.131 This section draws significantly

on Dodman, 2009.132 Gottdiener and Budd, 2005.133 McGregor et al, 2006.134 Angel et al, 2005.135 Rabinovitch, 1992.136 UNFPA, 2007.137 Angel et al, 2005.138 Brown et al, 2008, pp11–12. 139 Newman and Kenworthy, 1999.140 Brown et al, 2008, p12.141 Satterthwaite, 1999.142 Gottdiener and Budd, 2005.143 Newman and Kenworthy, 1989.144 Brown and Southworth, 2008.145 VandeWeghe and Kennedy,

2007.146 Norman et al, 2006.147 ‘The “urban heat island” effect

is caused by day time heatbeing retained by the fabric ofthe buildings and by a reduc-tion in cooling vegetation... In

tropical cities, the meanmonthly urban heat islandintensities can reach 10°C bythe end of the night, especiallyduring the dry season’ (Kovatsand Akhtar, 2008, p165).

148 Ewing et al, 2008.149 Mayor of London, 2007.150 Coutts et al, 2008.151 Campbell-Lendrum and

Corvalan, 2007.152 The impacts of climate change

on cities are discussed furtherin Chapter 4.

153 Neuman, 2005.154 Jabareen, 2006.155 Andrews, 2008.156 Burdett et al, 2005, p4.157 Bertaud et al, 2009.158 Bertaud et al, 2009, p29. At

least two reasons help toexplain this: companies do nothire based upon who liveswithin their business areas, andeconomic realities preventpeople from restricting theirjob searches to only thosebusinesses that are withinwalking or biking distancesfrom their homes.

159 Mayor of London, 2007.160 See the section on ‘Industry’

above.161 Weber et al, 2008.162 Walker and King, 2008.163 Compiled from data presented


164 See note 10.165 Dhakal, 2008.166 VandeWeghe and Kennedy,

2007.167 Referred to as ‘Annex I

countries’ in the Kyoto

Protocol.168 See Chapter 2.169 See note 110.170 Referred to as ‘non-Annex I

countries’ in the KyotoProtocol.

171 As seen in the case of SãoPaulo, Brazil (see Box 3.3; andDubeux and La Rovere, 2010).

172 This is discussed in more detailin Chapter 5.

173 Rees, 1992; Rees andWackernagel, 1998;Wackernagel et al, 2006;Girardet, 1998.

174 Rees, 1992, p121.175 Hertwich and Peters, 2009.176 Hertwich and Peters, 2009.177 Dhakal, 2004.178 Bai, 2007, p2.179 Bastianoni et al, 2004.180 Peters, 2008.181 Satterthwaite, 1997b.182 Halweil, 2002; Murray, 2005.183 Hendrickson, undated.184 Garside et al, 2007.185 Peters, 2008.186 Adger, 2001.187 Terry, 2009.188 Johnsson-Latham, 2007.189 See the section on ‘The scale

of urban emissions’.190 Dhakal, 2008.191 Women’s Environment

Network, 2010.192 Patt et al, 2009. See also

Chapters 4 and 6.193 Dhakal, 2008.194 Newman, 2006.195 Satterthwaite, 2008a.196 Satterthwaite, 2009.197 See Chapter 5.


Climate change impacts are now well documented andtechnological advancement has led to a clearer understand-ing of future risks and impacts. With increasing urbanization,understanding the impacts of climate change upon the urbanenvironment will become ever more important. Evidence ismounting that climate change presents unique challengesfor urban areas and their growing populations. Where urbanareas grow rapidly without regard to current and futureresource demands and climate change, large numbers ofpeople and their assets can find themselves vulnerable to arange of disruptive and damaging risks.

These impacts extend far beyond the physical risksposed by climate change, such as sea-level rise and extremeweather events. Cities could face difficulties in providingeven the most basic services to their inhabitants as a resultof climate change. Climate change may affect water supply,ecosystem goods and services, energy provision, industryand services in cities around the world. It can disrupt localeconomies and strip populations of their assets and liveli-hoods, in some cases leading to mass migration. Suchimpacts are unlikely to be evenly spread among regions andcities, across sectors of the economy or among socio-economic groups. Instead, impacts tend to reinforce existinginequalities; as a result, climate change can disrupt the socialfabric of cities and exacerbate poverty.

Although there is a burgeoning literature document-ing climate change impacts in various cities, there are fewcomprehensive studies that evaluate the wider implicationsfor cities across the globe. The purpose of this chapter is toidentify and discuss the impact of climate change on cities,where an ‘impact’ is defined as a specific effect on natural orhuman systems, either positive or negative, that results fromexposure to climate change.1 The first section describes thephysical climate change risks faced by cities and the extentof their variation across cities. ‘Risk’ is defined here as thecombination of the magnitude of the impact with the proba-bility of its occurrence.2 The direct and indirect physical,economic, social and health impacts of these changes incities are then reviewed in the context of existing vulnerabil-ities. Accordingly, impacts upon urban physical infra-structure, economies, public health and security arediscussed, keeping in mind the differential impact of climatechange upon specific vulnerable groups. The chapter then

identifies key indicators of vulnerability to climate change forurban residents and cities themselves. Finally, the lastsection offers some conclusions and lessons for policy.

CLIMATE CHANGE RISKSFACING URBAN AREASAtmospheric and oceanic warming as a result of human activ-ities has been observed over the past several decades.3

Climate research has illuminated the link between globalwarming and the alteration of the Earth’s water cycle, whichhas led to changes in precipitation frequency and intensity,cyclone activity, glacial melt and sea-level rise. These physi-cal changes, and the associated responses of ecosystems andeconomies, have discernible implications for cities world-wide, although these implications are characterized by widegeographical variation. Many of these changes assume agradual building of climate impacts and are becoming areality already; however, a not yet fully explored implicationrelates to the possible effects of abrupt climate changeevents (see Table 4.1).

This section describes the observed and predictedtrends and geographical variations in physical climate changerisks that confront urban settlements, including sea-levelrise, tropical cyclones, heavy precipitation events, extremeheat events and drought. The local conditions generated bycities as a result of heat-island effects are also discussed,underscoring the exacerbated risks and unique challengesfaced by the urban environment. The discussion in thischapter has been restricted to risks that have direct andindirect impacts upon urban settlements, and can beaddressed through local planning and governance.

Sea-level rise

Sea-level rise refers to the increase in the mean level of theoceans.4 Average sea levels have been rising around theworld during recent decades, but with significant regionalvariation. The average rate of rise accelerated from 1.8mmper year between 1961 and 2003 to 3.1mm per yearbetween 1993 and 2003.5 Sea-level rise has occurred fastestin the central Pacific region away from the Equator, the

Climate changepresents uniquechallenges for urbanareas and theirgrowing populations

C H A P T E R

THE IMPACTS OF CLIMATE CHANGEUPON URBAN AREAS

4

northeast Indian Ocean and in the North Atlantic along thecoast of the US. The Equatorial western Pacific, centralIndian Ocean and Australia’s northwest coast have experi-enced the lowest rates of rise.6 The Intergovernmental Panelon Climate Change (IPCC) predicts that global sea levels willcontinue to rise anywhere from 0.18 to 0.59m above 1980to 1990 levels by the end of the 21st century.7

Thermal expansion, or the increase in volume ofocean water as it warms, is considered to be the leadingcause of sea-level rise; but melting ice sheets may becomeever more important in the future.8 An additional factorcontributing to rising sea levels is melting ice from glaciersand land masses such as Greenland and Antarctica. Since1978, the total area of Arctic sea ice has declined by anaverage of 2.7 per cent each decade.9 Satellite surveys overWest Antarctica show glacial melting consistent with a rateof sea-level rise of 0.2mm per year and indicate that meltinghas accelerated during the early 2000s compared to the late1990s.10 Estimates of sea level rise due to ice loss fromAntarctica and Greenland from 1993 to 2003 are about0.21mm per year for both; but loss of these sheets in thefuture, even partially, could greatly alter the projections ofsea-level rise.11

Studies of past warming events suggest that theAntarctic and Greenland ice sheets melt rapidly in responseto warming, and could contribute to sea-level rise exceeding1m per century.12 Given that some physical processes ofglacial ice melt are not yet well understood by climate scien-tists, it has been difficult to provide an estimate of the upperbounds of sea-level rise.13 When considering what is knownabout glacial ice dynamics in tandem with the record of pastice-sheet melting, however, it is possible that the rate offuture melting and related sea-level rise could be faster thanwidely thought. There may be temperature thresholds or‘tipping points’ that accelerate melting to rates not yetexperienced in modern times.

The direct effects of sea-level rise include increasedstorm flooding and damage, inundation, coastal erosion,increased salinity in estuaries and coastal aquifers, risingcoastal water tables and obstructed drainage. However, agreat many indirect impacts are also probable (e.g. changesin the functions of coastal ecosystems and in the distributionof bottom sediments). Since ecosystems such as wetlands,mangrove swamps and coral reefs form natural protectionsfor coastal areas, changes to or loss of these ecosystems willcompound the dangers faced by urban coastal areas.

Sea-level rise is a serious concern for coastal cities asrising water levels and storm surges can cause propertydamage, displacement of residents, disruption of transporta-tion and wetland loss. This is especially so in the low-elevation coastal zone which, as indicated in Chapter 1,refers to the continuous area along coasts that is less than10m above sea level. It is predicted that sea-level rise and itsassociated impacts will, by the 2080s, affect five times asmany coastal residents as they did in 1990.14 In coastalNorth African cities, a 1°C to 2°C increase in temperaturecould lead to sea-level rise exposing 6 to 25 million residentsto flooding. Sea-level rise projections from 2030 to 2050indicate that Egyptian cities in the Nile Delta will be severelyaffected, including Port Said, Alexandria, Rosetta andDamietta.15 Low-lying coastal cities such as Copenhagen(Denmark), which lies at only 45m above sea level, will beespecially vulnerable to sea-level rise. Many small islandcommunities in the South Pacific are also highly vulnerableto rising sea levels. In fact, there is concern that sea-levelrise and flooding will occur to such an extent that somePacific islands will be completely submerged and entirecommunities displaced.16

The impacts of sea-level rise will continue to be feltglobally even if greenhouse gas (GHG) emissions are drasti-cally reduced given the time-lag between rising atmosphericand oceanic temperatures and the resulting sea-level rise.

Sea-level rise and itsassociated impactswill, by the 2080s,affect five times asmany coastalresidents as they didin 1990


Climate phenomena Likelihood Major projected impacts

Fewer cold days and nights Virtually certain Reduced energy demand for heating Warmer and more frequent hot days Virtually certain Increased demand for cooling and nights over most land areas Warmer temperatures Virtually certain Reduced disruption to transport due to snow, and ice effects on winter tourism

Changes in permafrost, damage to buildings and infrastructuresWarm spells/heat waves: frequency Very likely Reduction in quality of life for people in warm areas without air conditioning; impacts upon increases over most land areas elderly, very young and poor, including significant loss of human life

Increases in energy usage for air conditioningHeavy precipitation events: frequency Very likely Disruption of settlements, commerce, transport and societies due to floodingincreases over most areas Significant loss of human life, injuries; loss of, and damage to, property and infrastructure

Potential for use of rainwater in hydropower generation increased in many areasAreas affected by drought increase Likely Water shortages for households, industries and services

Reduced hydropower generation potentialsPotential for population migration

Intense tropical cyclone activity increases Likely Disruption of settlements by flood and high windsDisruption of public water supplyWithdrawal of risk coverage in vulnerable areas by private insurers (at least in developed countries)

Significant loss of human life, injuries; loss of, and damage to, propertyPotential for population migration

Increased incidence of extreme Likely Costs of coastal protection and costs of land-use relocation increasehigh sea level (excludes tsunamis) Decreased freshwater availability due to saltwater intrusion

Significant loss of human life, injuries; loss of, and damage to, property and infrastructurePotential for movement of population

Table 4.1

Projected impactsupon urban areas ofchanges in extremeweather and climateevents

Regardless of future emission levels, past emissions have setsea-level rise on a trajectory that will not stabilize for millen-nia. Figure 4.1 presents a theoretical picture of thisphenomenon: even if CO2 emissions are reduced and atmos-pheric concentrations stabilized, global air temperaturecontinues to rise for centuries and sea-level rise continuesfor millennia. Although emissions mitigation may preventever-worsening effects, the Earth is already ‘locked into’ acertain extent of climate change.17

Tropical cyclones

Tropical cyclones are weather systems associated withthunderstorms and strong winds that are characterized bytheir wind circulation patterns and a well-defined centre.18

These systems are so named because they originate near theEquator. Similar systems that originate in the mid-latitudes19

are referred to as ‘extra-tropical cyclones’. Both of theseresult in waves and storm surges (i.e. temporary offshorerise of water) that can damage property and threaten thesafety of individuals in the affected area. Cyclones are classi-fied as ‘storms’ when sustained wind speeds reach between63km to 118km per hour, while a hurricane is a tropicalcyclone with sustained wind speeds exceeding 118km perhour.20

Globally, tropical cyclones and extra-tropical stormshave been increasing in intensity since the 1970s asmeasured by their wind speed and other indices of a storm’sdestructive power. With the exception of the South PacificOcean, all tropical cyclone basins show increases in windspeed, wind strength and storm duration, with the greatestincreases in the North Atlantic and northern Indianoceans.21 Although tropical storms have not increased infrequency, extreme extra-tropical storms have increased innumber in the Northern Hemisphere since 1950.22

Accumulating evidence also suggests that thestrongest storms are getting stronger around the world. Themaximum wind speeds for satellite-observed cyclonesbetween 1981 and 2006 show the increasing occurrence ofcyclone wind speeds greater than the median. While thenumber of low-intensity hurricanes (category 1) hasremained approximately constant, they occur less often as a

percentage of the total number of hurricanes. On the otherhand, hurricanes in the strongest categories (4 and 5) havealmost doubled in number and in proportion (from around20 per cent to around 35 per cent during the same period).These changes have been observed in all of the world’socean basins.23

Although the relationship between temperature andformation of storm systems is not completely understood,increased temperature does correlate with increased occur-rence of tropical cyclones and extra-tropical storms.24 Risingsea surface temperatures change the Earth’s water cycle,disrupting ocean currents and altering precipitation pat-terns, which may lead, in part, to the increases in stormintensity observed over the past several decades.25 Withglobal warming, potential intensity (i.e. the upper bound ofcyclone intensity) is predicted to increase in most regions oftropical cyclone activity.26

The implications of increased cyclone activity andintensity are far reaching for cities. Power outages duringstorms disrupt transportation, economic activity and supplyof potable water. Physical destruction caused by storms isoften extremely expensive to repair and results in fatalitiesand injuries to humans and wildlife. Furthermore, inunda-tion of water during storms can contaminate water supplieswith saltwater, chemicals and waterborne diseases.

Heavy precipitation events

Heavy precipitation events are defined as the percentage ofdays with precipitation that exceeds some fixed or regionalthreshold compared to an average ‘reference period ofprecipitation from 1961–1990’.27 On average, observationsindicate that heavy one-day and heavy multi-day precipitationevents have increased globally throughout the 20th centuryand these trends are very likely to continue throughout the21st century.28 Deviations from average weather patternshave been observed globally, with an increase in thefrequency of heavy precipitation events in most areas of theworld.29

Precipitation changes have been variable at theregional level. In the tropics, eastern North America,Northern Europe, and Northern and Central Asia, precipita-

Tropical cyclonesand extra-tropicalstorms have beenincreasing in intensity since the1970s

67The Impacts of Climate Change upon Urban Areas

Figure 4.1

Relationship betweenCO2 emissions reduction, temperaturestabilization and sea-level rise

Note: After CO2 emissions arereduced and atmosphericconcentrations stabilize,surface air temperature contin-ues to rise slowly for a centuryor more. Thermal expansion ofthe ocean continues long afterCO2 emissions have beenreduced, and melting of icesheets continues to contributeto sea-level rise for manycenturies. This figure is ageneric illustration for stabi-lization at any level between450 and 1000 parts per million,and therefore has no units onthe response axis. Responsesto stabilization trajectories inthis range show broadly similartime courses; but the impactsbecome progressively larger athigher concentrations of CO2.

Source: IPCC, 2001a, p17

CO2 emissions peak0 to 100 years

100 yearsToday 1000 years

Mag

nitu

de o

f res

pons

e

Sea-level rise due to ice melting:several millennia

Sea-level rise due to thermal expansion:centuries to millennia

Temperature stabilization:a few centuries

CO2 stabilization:100 to 300 years

CO2 emissions

Time taken to reach equilibrium

tion increases have been documented in summer and winter,while summer precipitation decreases have been observedin mid-latitude regions. Severe decreases in both precipita-tion intensity and volume have been documented incountries such as Kenya, Ethiopia and Thailand.30 Likewise,the number of days during which more than 10mm ofprecipitation occurs has significantly increased over the 20thcentury across these countries and also in parts of Europe.31

General precipitation trends are expected to continuethroughout the 21st century, with average precipitationincreases very likely in the high latitudes and averagedecreases likely in the subtropical regions.32 More frequentheavy precipitation events will have far-reaching economicand social implications throughout the urban environment,especially through flooding and landslides.

n FloodingFloods are among the most costly and damaging disastersposing a critical problem to city planners as they increase infrequency and severity. The frequency and severity of flood-ing has generally increased during the last decade (comparedto 1950–1980 flood data), along with the frequency offloods that exceed levels that only typically occur once every100 years. Although there is variation in regional predic-tions, it is generally accepted that both trends will continue,especially in Asia, Africa and Latin America. Flood risk is alsoprojected to increase throughout Europe, particularly ineastern and northern regions and along the Atlantic coast.Assessments of vulnerability in Germany show that seaportcities Bremen and Hamburg may experience increasedprobabilities of flood risk from storms as climate changeprogresses, exposing billions of dollars of economic capital topotential damage.33 The Netherlands is one of the mostexposed countries in Europe, with nearly one third of thecountry located below average sea level in 2008.34 Densely

packed Amsterdam and Rotterdam are two out of ten citiesthat currently have the highest value of assets exposed tocoastal flooding.35

A recent ranking of cities based on vulnerability toflooding found that the top ten cities in terms of exposedpopulation were Mumbai (India), Guangzhou (China),Shanghai (China), Miami (US), Ho Chi Minh City (VietNam), Kolkata (India), Greater New York (US), Osaka-Kobe(Japan), Alexandria (Egypt) and New Orleans (US) (see Table4.2).36 The study also predicts that by 2070 almost all citiesin the top ten exposure risk category will be located in devel-oping countries (particularly in China, India and Thailand)because of the rapid population growth occurring in theseareas. On a national scale, the study predicts that theconcentration of future exposure to sea-level rise and stormsurges will be in the rapidly growing cities of developingcountries in Asia, Africa and, to a lesser extent, LatinAmerica. It is anticipated that the majority of high-exposurecoastal land area (90 per cent) will be located in only eightcountries: China, US, India, Japan, The Netherlands,Thailand, Viet Nam and Bangladesh.

In addition to the evident structural damage and lossof life that they cause, floods can short-circuit transformersand disrupt energy transmission and distribution; paralysetransportation; contaminate clean water supplies and treat-ment facilities; mobilize trash, debris and pollutants; andaccelerate the spread of waterborne diseases.37 Poorlyplanned informal settlements are especially vulnerable to theimpacts of flooding, as illustrated by the case of Mexico Citywhere flash flooding has increased dramatically over the pastdecade (see Box 4.1).

n LandslidesA landslide refers to a mass of material (e.g. rock, earth ordebris) that slips down a slope by gravity. The movement isoften rapid and assisted by water when the material issaturated.38 Vegetative cover, precipitation patterns, slopeangle, slope stability and slope-forming material all influencethe vulnerability of an area to landslides.39 Furthermore, thespatial distribution of landslides suggests a correlationbetween rapid land-use change and areas affected bylandslides and mudflows.40 Urban expansion and the clear-ing of vegetation for building and road construction can leadto soil erosion and weathering, and thereafter to loss of soilstability and the increased likelihood of landslides. Clearingvegetation interferes with the capacity for absorption ofrainfall, which results in runoff and gully erosion. Also, assettlements develop, vegetation is replaced with paved orhard pack areas and rainwater is channelled through prefer-ential flow channels instead of natural pathways, whichincreases the water’s erosive power.

The risk from landslides is also likely to increase asurban development continues on marginal and dangerouslands. With rapid urbanization, populations, especially theurban poor, increasingly settle in areas that are prone tohazardous landslides and are unsuited for residential devel-opment.41 City growth, chronic poverty, urban landspeculation, insecure tenure, inadequate urban infrastruc-ture investment, and poor urban planning policies contributeto continued development in vulnerable areas.42

The concentration offuture exposure tosea-level rise… willbe in the rapidlygrowing cities ofdeveloping countriesin Asia, Africa and,to a lesser extent,Latin America


Box 4.1 Increased incidence of flash flooding in Mexico City

The greater metropolitan area of Mexico City is one of the largest and most densely populatedurban settlements in the world, containing an estimated 19.5 million residents at a populationdensity of 3584 persons per square kilometre in 2010. The city and its residents have becomeincreasingly vulnerable to flooding and related impacts of climate change over the past century.Annual rainfall in Mexico City increased from 600mm during the early 20th century to over900mm towards the end of the century. Likewise, the annual incidence of flash flooding hasincreased from one to two annual floods, to six to seven annual floods over the same timeperiod. On 2 August 2006, for example, a rainfall of 50.4mm in only 36 minutes caused severeflooding in the southern and western parts of the city. The incidence of flash flooding isexpected to continue to rise due to climate change-related increases in the frequency of heavyprecipitation.

Higher precipitation is associated with an increased frequency of flash flooding, whichencompasses a wide range of conditions that threaten life and property, including submergedroads, overflowing rivers and mud- or rock-slides. Flooding damage including injury, death,property loss and water contamination are exacerbated by the infrastructure and developmentpatterns in Mexico City. Informal settlements are often located in areas prone to flooding andlandslides and, thus, particularly vulnerable. Inadequate drainage in these areas results in theaccumulation of trash and debris that poses serious hazards to human health when floodingoccurs. Poorly maintained and aging water drainage and sanitation systems throughout the cityworsen the impacts of heavy rains and flash flooding, and make it more difficult for communitiesto recover.

Source: Ibarrarán, 2011

Faulty construction methods and missing or inade-quate infrastructure design prevalent throughout informalsettlements further contribute to slope degradation, increas-ing the risks of landslides. Construction practices, such ascut and fill, which move soil from one part of a site toanother, increase the risk of a landslide, which, in turn, hasbeen shown to weaken slope stability and increase the likeli-hood of a further landslide.43 Recent estimates suggest that32.7 per cent of the world’s population live in slums,44

which are often situated in marginal and dangerous areas(i.e. steep slopes, floodplains and industrial areas).45 In citiessuch as Dhaka (Bangladesh), residents of informal settle-ments inhabit slopes surrounding the urban core, puttingthemselves at risk from flash floods and landslides.46

Similarly, in Mexico City, landslides often adversely affectslum residents.47 However, wealthy urban residents alsooccupy areas vulnerable to landslides primarily for aestheticreasons, as illustrated by the case of Los Angeles, US.48

An increasing frequency of landslides will have avariety of direct and indirect impacts in urban areas. Damageto infrastructure can be substantial, resulting in high mainte-nance and repair costs. Indirect impacts as a result of thisdamage, such as constrained movement of goods andservices, drive costs higher.

Extreme heat events

Heat waves are typically defined as extended periods ofhotter than average temperatures, although the precisetiming and temperature differential varies regionally.49 Thelack of specificity in the definition of an extreme heat eventor heat wave is due to the importance of local acclimatiza-tion to climate, which varies geographically. Previousresearch shows that populations in different locations havevarying abilities to deal with temperature extremes. Forexample, studies in Phoenix (US) have found no statisticallysignificant relationship between mortality rates and hightemperatures below 43°C, while in Boston (US), an increasein the rates of mortality is observed at 32°C.50 Several expla-nations exist for this phenomenon in Boston, includingbehavioural factors. Extremely high temperatures occurinfrequently and, as a result, residents do not have theproper level of preparedness for heat waves. Also, Boston hasextremely cold winters so a large percentage of homes arebuilt from heat-retaining red brick and few homes havecentral air conditioning.51 Consequently, during extremeheat events, ambient air temperature inside Boston homescan be dangerously high.

As a result of climate change, extreme heat events arepredicted to become more frequent, intense and longerlasting over most land areas (see Box 4.2).52 Some of theregions where more severe heat waves are expected in thefuture, due to increasing concentrations of atmosphericGHGs, include North America (particularly in the southernand north-western parts of the US) and Europe.53

Communities dependent upon glacial melt water alsostand to be negatively affected by changes in the distributionof extreme heat. As air and ocean temperatures rise and theincreasing frequency of heat waves changes stream flows,glaciers around the world will continue to shrink, threaten-

ing the one sixth of the world’s population dependent uponglacial melt water.54 In a number of South Americancountries with communities dependent upon glacial meltwater, water stress55 could increase as small glaciers disap-pear due to warmer temperatures and less snowfall. Changesin precipitation and the rapid loss of glacial mass in thisregion will significantly affect water availability for citiesacross the region – for example, Quito (Ecuador), Lima(Peru) and Bogotá (Colombia) – both for human consumptionand electricity generation. Communities dependent uponglacial melt water in China and Pakistan could also benegatively affected by shrinking glaciers.56

While physical climate changes can impact upon bothrural and urban areas, urban settlements generate uniquelocal conditions that interact with heat events. Compared torural areas, cities tend to have higher air and surface temper-atures due to the urban heat-island effect: the tendency ofcities to retain heat more than their surrounding ruralareas.57 For the average developed country city of 1 millionpeople, this phenomenon can cause air temperatures thatare 1°C to 3°C higher than the city’s surrounding area. Atnight, when urban heat-island effects are strongest, tempera-ture differences can reach 12°C.58 By increasingtemperatures, urban heat-island effects can aggravate theheat-related negative implications of climate change andimpose costly energy demands on urban systems as theyattempt to adapt to higher temperatures.59 The degree ofthese effects is not uniform across cities. The physical layoutof a city, its population size and density, and structuralfeatures of the built environment all influence the strengthof the urban heat-island effect. For example, the tendency

Urban settlementsgenerate uniquelocal conditions thatinteract with heatevents


Box 4.2 Extreme heat event trends in the US and Europe

Around the world, extreme heat events are predicted to become more intense, more frequentand longer lasting. In general, the increasing frequency of extreme heat events is likely to affectcities in colder regions because of a lower saturation of cooling technologies, heat retentiondesign of the existing building stock and cultures underprepared for extreme heat events:a

• On average in Chicago, 1.09 to 2.14 heat waves occur per year, whereas by 2080 to 2099the region could see heat wave frequency increasing to 1.65 to 2.44 per year. Also, theduration of heat waves may increase from 5.39 to 8.85 days today, to 8.47 to 9.24 days bythe same time.b

• Today, Paris averages 1.18 to 2.17 heat waves per year, which is expected to increase to1.70 to 2.38 per year by the end of the century. The average duration of a heat wave isexpected to increase from 8.33 to 12.69 days, to 11.39 to 17.04 days within thistimeframe.b

• In the north-eastern US, cities typically experience 10 to 15 days with temperatures above32°C and 1 or 2 days with temperatures above 38°C. However, by the end of the century,cities such as Philadelphia, Boston and New York can expect between 30 and 60 days eachyear with temperatures over 32°C, and between 3 and 9 days with temperatures over38°C, depending on the emissions scenario.c

• In some parts of Switzerland, the average monthly temperatures were as much as 6°Cabove monthly averages in June and August 2003, when Europe experienced a major heatwave. It is likely that future climate conditions will resemble the summer of 2003 morethan current conditions. Basel (Switzerland) could experience as many as 40 days above30°C, as compared to 8 days today.d

Sources: a Basu and Samet, 2002; b Meehl and Tebaldi, 2004; c UCS, 2006; d Beniston and Diaz, 2004

for French, Italian and Spanish cities to have stronger heat-island effects has been linked to their compactness andlimited area of green space compared to other Europeancities.60

Extreme heat events negatively impact upon humanhealth and social stability, increase energy demand andaffect water supply. The costs of water treatment are likelyto increase as high temperatures increase water demand. Atthe same time, water quality could decline as water pollu-tion becomes increasingly concentrated.61 Heat waves aremore likely to impact upon vulnerable populations, includ-ing the elderly, very young, individuals with pre-existinghealth conditions and the urban poor. The urban poor indeveloped countries are especially at an increased risk from extreme heat events because of their low adaptivecapacity.62

Drought

Drought can be defined as a phenomenon in which precipita-tion is significantly below normal levels, which leads tohydrological imbalances that negatively affect land resourcesand production systems. It can refer to moisture deficits inthe topmost metre of soil (i.e. agricultural drought), pro-longed deficits of precipitation (i.e. meteorological drought),below-normal water levels in a body of water (i.e. hydrologi-cal drought) or any combination of these.63 Droughts canresult from a number of different factors. In the westernparts of the US, drought conditions have emerged largely asa result of decreases in snow pack, while areas in Australiaand Europe have seen drought conditions due to extremelyhigh temperatures associated with heat waves.64 In Asia,increasing frequencies of droughts are likely to result fromincreasing temperatures.65

The IPCC concluded that not only have droughtsbecome more common in the tropics and subtropics since1970 but, more likely than not, humans have contributed tothis trend.66 Since the 1950s, significant drying trends havebeen observed across the Northern Hemisphere in portionsof Eurasia, Northern Africa, Canada and Alaska. The South-ern Hemisphere over the same time period has experiencedslight drying trends. During the last century, mean precipita-tion in all four seasons of the year has tended to decrease inall of the world’s main arid and semi-arid regions: northernChile, the Brazilian northeast and northern Mexico, WestAfrica and Ethiopia, the drier parts of Southern Africa, andwestern China.67 In Yemen, the capital city Sanaa is expec-ted to run out of water by the year 2020, spurring massmigration and potential conflicts.68

The amount of land area under extreme droughtconditions69 is expected to increase further in the future as aresult of changes in precipitation.70 Currently, as much as 1per cent of all land area is considered as being under extr-eme drought conditions.71 By 2100, this could increase to asmuch as 30 per cent.72 Drying is likely to occur in continen-tal interiors during summer periods, especially in thesubtropics, low and mid-latitudes.73 More intense and multi-annual droughts have occurred in sub-humid regions,including Australia, western US and southern Canada.74 In

Africa, one third of all people already live in drought-proneareas and, by 2050, as many as 350 to 600 million could beaffected by drought.

Drought affects urban areas in numerous ways. It cancompromise water quality and increase the operating costsof water systems while reducing their reliability.75 Waterstress is likely to increase as a result of changes in precipita-tion and the consequent decline in water supply and qualityand increased demand for water.

IMPACTS UPON PHYSICALINFRASTRUCTUREThis section describes the physical damage caused by climatechange and their implications for urban areas. Climatechange has direct effects on the physical infrastructure of acity – its network of buildings, roads, drainage and energysystems – which, in turn, affects the welfare and livelihoodsof its residents. The severe weather events and relatedhazards outlined above can decimate roads, homes andplaces of business. These impacts will be particularly severein low-elevation coastal zones where many of the world’slargest cities are located. Although they account for only 2per cent of the world’s total land area, approximately 13 percent of the world’s urban population live in these zones.76

Residential and commercial structures

Substantial damage to residential and commercial struc-tures is expected with the increasing occurrence of climatechange-related hazards and disasters. In this regard, flood-ing is one of the most costly and destructive naturalhazards, and, as indicated earlier, one that is likely toincrease in many regions of the world as precipitation inten-sity increases. In the absence of adaptive infrastructurechanges, vast increases in spending on flood damage incities are expected due to climate change.77 In Boston (US),for example, river flooding could cause up to US$57 billionin damage by 2100 without adaptive measures, anestimated US$26 billion greater cost than would occur inthe absence of climate change. Many of the homes likely tobe affected are low-value houses that may not be insuredagainst predicted damage. As in other areas of the world,the distributional nature of these impacts remains achallenge.78

The terms ‘100-year flood’ and ‘500-year flood’ aresometimes used to describe the flood risk to residents livingin particular areas. These terms refer to the probability withwhich the flood occurs. For example, if there is a 1/100chance of a given city experiencing a flood at a rate of 425cubic metres per second, this level of flooding will occur, onaverage, once every 100 years. Likewise, a flood rate thatoccurs with a probability of 1/500 is referred to as a 500-yearflood.79 The terms 100-year floodplain and 500-year flood-plain refer to the geographic areas that are affected during100-year and 500-year floods, respectively.

Today, around 40 million people live in a 100-yearfloodplain. By 2070, the population living at this risk level

The amount of landarea under extremedrought conditionsis expected toincrease further inthe future as a resultof changes in precipitation

Substantial damageto residential andcommercial structures isexpected with theincreasingoccurrence ofclimate change-related hazards anddisasters


could rise to 150 million people. The estimated financialimpact of a 100-year flood would also rise from US$3 trillionin 1999 to US$38 trillion by this time. Miami (US) is themost exposed city today and will remain so in 2070, withexposed assets rising from approximately US$400 billiontoday to over US$3.5 trillion. Over the coming decades, theunprecedented growth and development of Asian megacitieswill be a key factor driving the increase in coastal flood riskglobally. By 2070, eight of the most exposed cities will be inAsia (see Table 4.2).

Damage to residential and commercial structures isnot limited to large-scale disasters. Slow-onset climate-change physical risks such as sea-level rise can also affect thebuilt environment in a number of ways. Coastal erosion islikely to affect cities around the world particularly in themega-deltas of South, East and Southeast Asia, Europe andthe North American Atlantic coast.80 In the US, a 0.3m sea-level rise81 would erode approximately 15m to 30m ofshoreline in New Jersey and Maryland, 30m to 60m in SouthCarolina and 60m to 120m in California.82 Parts of Louisianaand Mississippi along the Gulf Coast of the US are physicallysusceptible to loss of land from the combined effects oferosion and sea-level rise, whereas some areas of Florida andTexas are susceptible due to social and economic factors ofvulnerability.83 Coastal erosion and saltwater intrusion canruin buildings and render some areas of land uninhabitable,which is a particular problem for coastal cities that rely ontourism as a major part of their economies. Mombasa(Kenya), for instance, could lose approximately 17 per centof its land from a 0.3m rise in sea level, causing the loss ofhotels, cultural monuments and beaches that drawtourists.84

Subsidence, or the downward shift of the Earth’ssurface, is another ‘slow-onset’ factor that poses a risk toresidential and commercial structures in cities. Subsidencecan be caused or exacerbated by overexploitation of ground-water resources during hot, dry periods which are likely tooccur more frequently with climate change. Subsidence canbe as rapid as 1m per decade, resulting in significant damageto pipelines, building foundations and other infrastructure.85

In England, increased subsidence caused by drier, hottersummers led to significantly greater homeowner insuranceclaims throughout the late 1990s.86 Subsidence has beennoted in several megacities throughout the world, includingTokyo (Japan), Dhaka (Bangladesh), Jakarta (Indonesia),

Kolkata (India), Metro Manila (the Philippines), Shanghai(China), Los Angeles (US), Osaka (Japan) and Bangkok(Thailand).87 During the late 1980s, Tianjin (China) experi-enced as much as 11cm of subsidence per year.88 Portions ofthe Osaka-Tokyo metropolitan region would be under wateras a result of subsidence if it were not for coastal defencesand extensive flood-control systems.89

Accumulating damage to residential and commercialbuildings due to sun exposure and low-intensity wind andprecipitation may increase in some areas of the world asregional weather patterns change. In London (UK), morefrequent heavy rains and higher peak wind speeds (predictedfor the 2050s and 2080s) are expected to damage buildings,particularly those that are aging. Wind and rain damage cancause hazards to people in the vicinity of affected buildingsand may lead to additional economic losses if commercialbuildings need to close for repairs.90 Studies on NewZealand indicate that commercial buildings throughout thecountry will experience increased damage in the face ofwind damage, coastal flooding and extreme temperatures.91

In the Arctic region, human settlements are expected to faceserious challenges with the melting of permafrost, which isessential for the stability of buildings and infrastructure.92

Transportation systems

Climate change impacts frequently disrupt transportationsystems through weather conditions that have immediateconsequences for travel and damage, causing lasting serviceinterruptions. In coastal cities, in particular, sea-level risecan inundate highways and cause erosion of road bases andbridge supports. For example, along the Gulf Coast of the USan estimated 3862km of roadway and nearly 402km of railtracks may become permanently submerged during the next50 to 100 years due to the combined impacts of subsidenceand sea-level rise. Total economic impacts resulting from thisloss could reach hundreds of billions of dollars when consid-ering the commercial and industrial activities that take placein the gulf’s many seaports, highways and railroads.93 Forinstance, weather-related highway accidents translate intoannual losses of at least US$1 billion annually in Canada,while more than one quarter of air travel delays in the US areweather related.94 In India, landslides in July 2000 resultedin 14 days without train service, leading to estimated lossesof US$2.2 million.95

Unprecedentedgrowth and development ofAsian megacitieswill be a key factordriving the increasein coastal flood riskglobally

Climate changeimpacts frequentlydisrupt transportationsystems


Ranking by population exposure Ranking by value of property and infrastructure assets exposure

Kolkata (India) Miami (US)Mumbai (India) Guangzhou (China)Dhaka (Bangladesh) New York (US)Guangzhou (China) Kolkata (India)Ho Chi Minh City (Viet Nam) Shanghai (China)Shanghai (China) Mumbai (India)Bangkok (Thailand) Tianjin (China)Rangoon (Myanmar) Tokyo (Japan)Miami (US) Hong Kong (China)Hai Phong (Viet Nam) Bangkok (Thailand)

Source: Nicholls et al, 2008

Table 4.2

Exposure to floods in cities

Heavy precipitation and its effects in the form offlooding and landslides can cause lasting damage to trans-portation infrastructure, such as highways, seaports andbridges. In 1993, flood damage to transport systems inMidwestern US resulted in major traffic disruption fromMissouri to Chicago for nearly six weeks.96 Delays in publictransportation including rail and air services often occurduring heavy rains and storms. A study of the Konkan railwaynetwork in western India that facilitates trade and energyservices between Mumbai and Mangalore revealed that 20per cent of major repairs were due to climatic factors. Eachyear, US$1.1 million is spent to reduce the number oflocations on the network that are vulnerable to heavyrains.97 Heavy rains also affect the long-term functionalcapacity of airport runways, which will lead to the need forincreased maintenance considerations in those areas whereprecipitation is likely to increase.

Increasingly higher temperatures, particularly longperiods of drought and higher daily temperatures, compro-mise the integrity of paved roadways and necessitate morefrequent repairs. For instance, by 2080, road buckling,rutting and speed restrictions are anticipated to increase inLondon (UK) as average temperature increases melt asphaltand accentuate subsidence.98 Extreme heat also leads tojoint expansion on bridges and rail deformation, whichrequire costly maintenance and, in worst-case scenarios,could cause major accidents. Drier conditions can furthercause lower water levels in rivers and interrupt trade andtransportation via inland water routes.

Besides potentially endangering lives, the destructionor damage of transportation systems and lasting servicedisruptions greatly affect nearly all aspects of urban life.Disruptions in public transportation can limit the ability ofresidents to get to work, leading to declines in economicproductivity. By 2100, as a result of increases in climaticchange-related delays, motorists in Boston (US) could spend80 per cent more time on roadways and 82 per cent moretrips could be cancelled.99 Interruptions in the transport offuel for energy production can also lead to service disrup-tions in the electricity sector.

Energy systems

By their very nature, cities are centres of high demand forenergy and related resources. Climate change is likely to

affect both energy demand and supply. The combination ofurban population growth, changing local weather conditions,urban heat-island impacts and economic growth has thepotential to substantially increase demand for energy (seeBox 4.3). Although the relationship between energy demandand local weather fluctuations has long been confirmed,relatively few studies have taken on the task of examininghow longer-term climate changes affect the energy sector.

Energy demand increases will depend upon regionalclimate differences. Higher winter temperatures can lead todecreased heating use, while increased summer tempera-tures can lead to increased need for cooling. In turn, greateruse of air conditioning due to rising temperatures canworsen the urban heat-island effect and further increase thecooling demand in urban areas.100 Studies indicate thatthere is high regional variation in energy demand sensitivityto climate change even in similar climates. In the US, forexample, neighbouring states Florida and Louisiana havedifferent patterns of industrial and residential energy use.101

Likewise, an assessment of several US regions reveals uniquedemand sensitivities among four cities (Seattle, Minneapolis,Phoenix and Shreveport) and different directions of demandchange between states with differing average local weatherconditions.102 The use of aggregate data, however, may bemisleading because even if there is no net increase inregional demand, great increases in local demand for coolingmay still require infrastructure investment, reconsiderationof energy portfolios and energy conservation mechanisms.

Climate change will also affect energy generation anddistribution. Across Africa, hydroelectric power generationis likely to be restricted with the more frequent occurrenceof drought periods. For instance, climate change simulationssuggest that the planned Batoka Gorge Hydroelectric Projecton the Zambezi River, a joint project between Zambia andZimbabwe, will be negatively affected if the mean monthlyriver flow significantly declines.103 However, the worldwideimpacts of climate change upon hydroelectricity productionare variable. For example, electricity output from hydroelec-tric projects in Scandinavia and northern Russia is predictedto increase due to trends in future precipitation patterns andtemperature.104

Reduced stream flows due to climate change mayfurther reduce the availability of cooling water for thermaland nuclear power plants.105 In Europe, the 2003 heat wavewas accompanied by annual rainfall deficits of as much as300mm.106 Drought conditions had impacts upon powergeneration and several power plants were unable to physi-cally or legally divert water because of extremely low streamflow, resulting in reductions in power generation. Forinstance, nuclear power plants in parts of France were forcedto shut down as stream levels became too low or watertemperatures exceeded environmental standards. Sixnuclear reactors, as well as a number of conventional powerplants, were given exemptions to continue operating in spiteof exceeding legal limits.107 In terms of energy distribution,electricity transmission infrastructure may become increas-ingly vulnerable to damage and interference as storms andflooding become more frequent and intense.108

Destruction ordamage oftransportationsystems and lastingservice disruptionsgreatly affect nearlyall aspects of urbanlife

Climate change islikely to affect bothenergy demand andsupply


Box 4.3 Global changes in energy demand

• Between 2010 and 2055 in the US, energy demand may increase capacity requirements forthe electricity sector by 14 to 23 per cent over demand trends in the absence of climatechange.a

• Daily peak energy loads for New York City (US) could increase by 7 to 13 per cent by the2020s, 8 to 15 per cent by the 2050s and 11 to 17 per cent by the 2080s.b

• By 2080, a 30 per cent increase in energy demand is forecast for Athens (Greece), largelyas a result of increasing air-conditioning use.c

• In Toronto (Canada), a 3°C increase in temperatures would result in increases in peakelectricity demand of 7 per cent and an increase of 22 per cent in the variability of peakdemand.d

Sources: a Linder, 1990; b Rosenzweig and Solecki, 2001; c Giannakopoulos and Psiloglou, 2006; d Colombo et al, 1999

Water and sanitation systems

The availability, treatment and distribution of water could beaffected by climate change as temperatures increase andprecipitation patterns change.109 On the one hand, climatechange is expected to compromise water supplies, particu-larly in areas where water stress is expected to increase. Indeveloping regions such as Africa, water stress is expectedto increase as a result of population growth and is likely to beexacerbated by climate change. However, the impacts willnot be uniform across the continent as populations in thenorth and south are expected to experience increases inwater stress, while those in the east and west are likely tosee a reduction in water stress.110

Water supplies can be reduced or increased throughchanges in precipitation patterns, reductions in river flows,falling groundwater tables and, in coastal areas, saline intru-sion in rivers and groundwater.111 For example, detecteddeclines in glacier volumes in parts of Asia and Latin Americaare already reducing river flows at key times of the year. Forcities located in the Andean valleys and in the Himalaya-Hindu-Kush region, this has substantial impacts upon waterflows and affects multiple human uses of water in theseareas, including reducing hydroelectric power generation.112

The expected changes in runoff and water availability are,however, projected to be regionally differentiated by 2050:increases by 10 to 20 per cent at higher latitudes and insome areas in the wet tropics (e.g. populous areas in tropicalEast and Southeast Asia), and decreases by 10 to 30 per centover areas in the mid-latitudes and dry tropics, some ofwhich are currently water stressed.

On the other hand, with rising temperatures, morefrequent extreme heat events and population growth in thefuture, demand for water in cities is expected to increase.113

Many areas of the world have been getting drier across allseasons; if the trend continues, water resource limitationswill become more severe.114 By 2030, summer water use inWashington, DC (US), is expected to increase between 13and 19 per cent relative to an increase from 1990 levelswithout climate change.115 In Cape Town (South Africa),water demand is simultaneously projected to increase withtemperature increases.116 In Nagoya (Japan), temperatureincreases could induce an increase of 10 per cent in wateruse.117 In Latin America, 12 to 81 million residents couldexperience increased water stress by the 2020s. By the2050s, this number could rise to 79 to 178 million.118

Stream flow supplying Melbourne (Australia) is likely todecline by 3 to 11 per cent by 2020 and 7 to 20 per cent by2050, compared to 1961 to 1990 averages, thereby affectingwater supplies. Concerns about drought and water demandincreases have also been raised in other cities such asAuckland, Adelaide, Canberra, Perth, Brisbane andSydney.119

Climate change-related changes in precipitation andsea levels can also affect the quality and treatment of waterin cities. Saltwater intrusion can occur more frequently incommunities experiencing sea-level rise and contaminateground and surface water, thus reducing the supply ofpotable water and spreading harmful pollutants throughouturban water systems. Cases of saltwater intrusion due to sea-

level rise have already been documented among most coastalcities across diverse environments, including eastern US(e.g. New Orleans), Latin America (e.g. Buenos Aires,Argentina), as well as both in the Yangtze River Delta inChina and the deltas of Viet Nam.120 Reduced precipitationand, thus, water supply can also cause saltwater intrusion.The city of Kochi (India) is located at 2m above sea level andis compromised by a network of rivers and canals. Saltwaterintrusion into these rivers is worsened during hot, dryperiods when evaporation increases the concentration ofsalts in the water, leading to economic losses and drinkingwater shortages.121

Furthermore, excess heat from buildings and roadsdue to the urban heat-island effect can be transferred tostorm water, thereby increasing the temperature of waterthat is released into streams, rivers, ponds and lakes. Higherwater temperatures, in conjunction with increased precipita-tion intensity and low flows, are predicted to exacerbatewater pollution, including through thermal pollution, whichcan promote algal blooms and increase bacterial and fungalcontent.122 Once they have been contaminated, it is, in mostcases, expensive to clean drinking water supplies.

Water supply infrastructure is capable of adapting tosmall changes in mean temperatures and precipitationamounts as water systems have been designed with sparecapacity for future growth.123 Still, many systems will needimprovements, such as building new reservoirs or extensionof water intake pipes to handle increasingly variable precipi-tation levels. In addition, water supply infrastructure isvulnerable to damage from extreme climate events such asfloods and storm surges, especially if it is adjacent torivers.124 In New York City (US), pumping stations and watertreatment facilities, including intake and outflow sites, arevulnerable to storm surges.125 Damage to water supply infra-structure, especially if electronics are damaged, can takeweeks to fix and can cost as much to repair as their initialconstruction costs, as was the case during flooding inMozambique during 2000.126

Climate change-related disasters can also affect sanita-tion systems in urban areas which already face seriouschallenges, especially in developing countries. Althoughaccess to improved water supply and sanitation has beenincreasing since 1990 in many areas of the world, there arestill large proportions of the population living in unsanitaryconditions.127 In 2006, 38 per cent of the world’s populationand nearly half of the developing world’s population lackedaccess to improved sanitation facilities, including flushtoilets, pit latrines or composting toilets.128 Access to sanita-tion infrastructure and services is likely to decline furtherdue to climate change-related risks, as in the case ofHurricane Mitch, which destroyed 20,000 latrines in1998.129

ECONOMIC IMPACTSThe increasing frequency and intensity of extreme climaticevents and slow-onset changes will increase the vulnerabilityof urban economic assets and, subsequently, the costs ofdoing business.130 Studies suggest that developing countries

The availability,treatment and distribution of watercould be affected byclimate change

Climate change-related disasters canalso affect sanitationsystems in urbanareas… especially indeveloping countries


typically suffer low economic losses but high human lossesas a result of climate change-related risks, while developedcountries suffer high economic costs and low human losses.However, recent events show that developed countries cansuffer high human costs as well, especially amongst theurban poor. Also, when economic impacts are expressed as ashare of the value of total assets or gross domestic product(GDP), economic costs incurred by developing countries mayalso be high and can result in increasing fiscal imbalancesand current account deficits due to increased borrowing andspending to finance recovery.131 This section explores theeconomic impacts of climate change within urban areas,including those related to economic sectors, ecosystemservices and livelihoods.

Sectoral economic impacts

Climate change will affect a broad range of economic activi-ties, including trade, manufacturing, transport, energysupply and demand, mining, construction and related infor-mal production activities, communications, real estate, andbusiness activities.132 Box 4.4 describes the cross-sectoraleconomic impacts of tropical cyclones in Dhaka (Bang-ladesh).

This section describes climate change impacts uponeconomic sectors – namely, retail and commercial services,industry, tourism and insurance – as these tend to operate inand around cities. Industrial infrastructure in coastal cities isparticularly vulnerable to sea-level rise and coastal storms.The effects of climate change on tourism are also considered

as it can be a part of the urban economy directly or depend-ent on it for services, including travel (e.g. airports, seaports,etc.) and supplies. Furthermore, climate impacts upon thetourism industry can induce migration from rural to urbanareas, thus increasing the demand for goods and serviceswithin urban areas.133

n Industry and commerceIndustrial activities can bear potentially high direct andindirect costs from climate change and extreme climateevents. Whether industries are located in the heart of urbanareas or in adjacent suburban or rural areas, they provideservices and resources that are vital to city function. Damageto industries due to climate events thus has direct andindirect impacts upon cities and their residents.

The direct effects of climate change and extremeclimate events on industry include damage to buildings,infrastructure and other assets. These effects are especiallysevere where industrial facilities are located in vulnerableareas, such as coastal zones and floodplains. For example,sea-level rise in coastal cities such as New Orleans (US) willpotentially necessitate the relocation of refineries, naturalgas plants and facilities, as well as supporting industries toless at-risk areas or further inland, at a substantial cost (seeBox 4.5).134 The indirect impacts of climate change upon industry include those resulting from delays and cancellations due to climate effects on transportation,communications and power infrastructure.135

Similarly, retail and commercial services are vulnera-ble because of supply chain, network and transportationdisruptions, and changes in consumption patterns.136 Anincreasing likelihood of flooding, coastal erosion and otherextreme events will stress and damage transport infrastruc-ture, as indicated earlier in this chapter, disrupt retail andcommercial services, and subsequently increase the costs ofdoing business.137 For example, in 2001, the Great Lakes–St Lawrence region of Canada experienced drought condi-tions that lowered river levels to such an extent that itslowed river traffic, which partially explains the reductionin volume of goods shipped through the Great Lakes thatyear.138 Similarly, the 2003 heat wave and drought acrossEurope resulted in record low river levels, which negativelyaffected the transportation of goods along inland water-ways.139

Changes in the regulatory environment, includingclimate change mitigation policies (e.g. carbon tax andemissions targets) could potentially raise the costs ofbusiness for industries, especially if they are energy inten-sive.140 For instance, the iron and steel industry is heavilydependent upon burning fossil fuels, with 15 to 20 per centof the production costs going towards energy. In the US, thepulp and paper industry is the second most energy-consum-ing industry.141

Industries dependent upon climate-sensitive inputsare also likely to experience changes in the reliability, avail-ability and cost of major inputs as a result of changes inclimate and climate mitigation policies. For instance, indus-tries dependent upon timber and agricultural inputs rely onan increasingly fragile resource because of changes in the

The increasingfrequency and intensity of extremeclimatic events andslow-onset changeswill increase thevulnerability ofurban economicassets


Box 4.4 Cross-sectoral impacts of tropical cyclones: The case of Dhaka, Bangladesh

Given that the majority of its land area is less than 6m above sea level, the population ofBangladesh and its assets are highly vulnerable to the impacts of tropical cyclones. Rising sealevels and increased prevalence of cyclones have been documented over the past decade, alongwith increased frequency and intensity of sudden and severe floods. Between 1991 and 2000,the country experienced 93 major disasters, resulting in nearly 200,000 deaths and costingUS$5.9 billion in damage to agriculture and infrastructure.

Storm surges cause massive damage to the city of Dhaka, which has experienced fourmajor floods in the past two decades, including one that submerged 85 per cent of the city. Inaddition to endangering lives, these events have multi-sectoral impacts that cause lasting damageto the economic and social fabric of the city. Disruption of activity in textiles, timber, food andagro-based industries results in massive economic loss. In 1998, it was calculated that totalindustry loss was more than US$66 million. All utility services essentially cease during floodingevents, and structural damage can cause lasting disruption of utility services such as watersupply, sanitation, waste and sewage management, telecommunications, and electricity and gassupplies.

The city’s adaptation efforts have been aimed at mitigating the impacts of extremeflooding events by expanding the Integrated Flood Protection Project, a programme funded bythe Asian Development Bank to improve flood protection structures, drainage and sanitation,and to resettle residents of slums into safer areas. Improving the drainage system and reinforc-ing the water system is a priority since the city’s water has become contaminated in the past,and acute drinking water crisis has been a major problem in post-flood efforts. There is also aninitiative to involve non-governmental organizations (NGOs), the business community andcommunity-based organizations to enhance aid in relief, recovery and rehabilitationprogrammes.

Source: Vaidya, 2010

incidence of pests and diseases. Climate change holds thepotential to shift the habitat of economically important treeand crop species, as well as changing the behaviour anddistribution of pests.142 The changing distribution of climate-sensitive inputs could result in increasing costs to industry,as industrial plants and their raw material inputs becomegeographically separated.

n Tourism and recreationThe tourism industry is highly dependent upon reliabletransportation infrastructure, including airports, ports androadways. Climate change has the potential to not only shiftregional temperature distributions, but also increase theincidence of severe weather events, which would increasetransportation delays and cancellations. Since recreationalactivities and tourism are often major sources of revenue forurban areas, when climate change impacts affect these activ-ities, local urban economies will incur monetary and joblosses (see Box 4.6).

Tourism in cities of high-latitude countries couldbenefit from a pole-ward shift143 of warmer conditions,increasing the area available for tourism activities.144

However, winter activities (i.e. skiing and snowmobiling) arelikely to become increasingly vulnerable because of climatechange-related declines in natural snowfall leading to fewerdays of snow cover.145 Across much of the north-easternregion of the US, climate change will result in fewer days ofnatural snow cover and, in spite of snow-making technology,ski areas will experience a decline in the length of theirseasons. To continue operating will necessarily mean anincrease in costs because manufacturing snow is both waterand energy intensive. Climate change will further result indeclining season length as reliable snow is pushed into upperlatitudes and higher elevations. As a result, the average

distance travelled to winter resources such as ski mountainsis expected to increase dramatically.146 The weakening of theski industry would also affect related support industries suchas hotels, restaurants and ski shops. The decline of winterrecreational opportunities can thus result in great economiclosses for those regions with economies heavily reliant onskiing and snowboarding.

The summer tourism industry across the temperatezone is thought to be resilient to increases in averagetemperatures because of the expectations of warm tempera-tures, as well as the availability of air conditioning.147

However, changes in the frequency and intensity of extreme

Industries dependent uponclimate-sensitiveinputs are also likelyto experiencechanges in the reliability, availability and costof major inputs


Box 4.6 Climate change impacts upon the tourism industry

• The annual number of tourists visiting Canada and Russia is estimated to increase by 30per cent as a result of a 1°C rise in temperatures.a

• The cost of climate change for Switzerland is estimated to be US$1.4 to $1.9 billion by2050 – of this amount, US$1.1 billion is from tourism alone. In Switzerland, 85 per cent ofski areas are considered as snow-reliable today; however, under climate change scenarios,only 44 per cent will remain snow reliable in the future. A number of communities inSwitzerland are heavily dependent upon winter tourism as it provides a significant portionof their income.b

• The Norwegian ski industry could be negatively affected by climate change as summertimeski destinations are expected to experience more rainy weather during the summermonths.c

• For Australia, a 3°C to 4°C increase in temperatures would cause catastrophic mortalityto a large percentage of the coral species that make up the Great Barrier Reef. Even with a1°C to 2°C increase in temperatures, between 58 and 81 per cent of the coral would bebleached every year. And because of the importance of the reef to Australian tourism, a US$32 billion industry, declines in reef health would negatively impact the tourism industry.d

Sources a Hamilton et al, 2005; b Elsasser and Bürki, 2002; c O’Brien et al, 2004; d Preston and Jones, 2006

Box 4.5 Economic impacts of Hurricane Katrina, US

The city of New Orleans is located on vulnerable lands at the mouth of the Mississippi River on the Gulf of Mexico. Due to its proximity tothe Mississippi and the gulf, the area has strategic economic importance for the petrochemical industry, as well as international trade. NewOrleans’s longstanding infrastructure and population centres have become increasingly at risk from climate events; coastal defences and otherland areas are subsiding as a result of groundwater withdrawal, man-made changes to the flow of the Mississippi River prevents silting and thebuild-up of new land, and the below sea-level elevation of much of the city requires continuous pumping of water.

In 2005, Hurricane Katrina caused extensive damage to physical infrastructure and the economies of the gulf coast region. Theeconomic losses were in the hundreds of billions of US dollars. An estimated 1.75 million property claims were filed, totalling more thanUS$40 billion. Over 250,000 claims were filed as a result of flood damage, which would have bankrupted the National Flood InsuranceProgram were it not given the right to borrow an additional US$20.8 billion.

In the Gulf of Mexico, over 2100 oil and natural gas platforms and 15,000 miles (24,140km) of pipeline were affected. A total of 115platforms were lost, with 52 suffering heavy damage; 90 per cent of total Gulf of Mexico oil production and 80 per cent of natural gas wereidled, with lost production equalling over 28 per cent of annual production. The damage to the petrochemical corridor, which produces half ofthe US supply of gasoline, caused disruptions in economic markets worldwide, resulting in the largest spike in oil and gas prices since theOrganization of the Petroleum Exporting Countries (OPEC) embargo of 1973. In the first two months following Hurricane Katrina, over390,000 people lost their jobs, with over half coming from low-wage earning jobs. As of 2006, only 10 per cent of businesses in New Orleanshad returned and reopened.

Before Hurricanes Katrina and Rita, which also happened in 2005, the port of New Orleans was the fourth largest port in the worldin terms of transported tonnage. However, as a result of the damage from hurricanes, port operations were halted for a period of time, whichforced a realignment of shipping destinations and functions that, because of the high cost of realignment, could become permanent.

Sources: Petterson et al, 2006; Wilbanks et al, 2007

weather events could negatively affect the perception ofsafety in these locations, environmental quality and tourisminfrastructure reliability. For example, in Southern Europe,along the Mediterranean coast, increasing water scarcity as aresult of climate change could negatively impact upon thetourism industry.148

Coastal areas, including those in cities, have oftenbeen extensively developed for tourism, leaving substantialinvestments in buildings and infrastructure at risk fromextreme climatic events, which would significantly affect theeconomies of small island states.149 Erosion as a result ofcoastal storms can cause beaches to recede by as much as5m, but can recover quickly through natural sand deposition.If sea-level rise is accompanied by stronger and morefrequent coastal storms, the costs of maintaining shore spacefor tourist activities could rise and reduce beach tourism forcities.150 The city of Rio de Janeiro (Brazil), for instance,popular, among other reasons, for its beaches, is vulnerableto sea-level rise and increased erosion. In the capital city ofEstonia, Tallinn, beachside resorts are particularly vulnerableto sea-level rise and storm surges, which could lead to moreerosion of the beaches and negatively affect tourism.151

Furthermore, extreme climate events can damage manyreefs and coastal ecosystems, resulting in decliningtourism.152 A 1°C rise in temperatures would result in morefrequent coral bleaching, with the coral recovering slowly,while a 2°C rise in temperatures would result in the annualbleaching of coral in many areas that might never recover.153

Tourism is an essential component of the localeconomy of many island countries in the Caribbean andelsewhere. In the eastern Caribbean, tourism accounts forbetween 25 and 35 per cent of the regional economy, onequarter of foreign exchange earnings and one fifth of all jobs.Each year, the region receives approximately 20 milliontourists. The economic dependence upon tourism has led tointensive development and siting of infrastructure (i.e.

hotels, roads, etc.) that tend to be densely packed alongcoastlines. As a result of changes in sea level and waveaction, the islands of the eastern Caribbean will experiencesubmergence of low-lying areas, including population cent-res, erosion of soft shores, increasing salinity of estuariesand aquifers, and more severe coastal flooding and stormdamage.154

n InsuranceThe insurance industry is vulnerable to climate change,particularly extreme climate events that can affect a largearea.155 Storms and flooding can cause significant amountsof damage and are often responsible for a large percentage oftotal losses, as illustrated in Box 4.7.156

Climate change could result in increasing demand forinsurance while reducing insurability. Insurance industrycatastrophe models forecast that annual insured claims andlosses are likely to significantly increase over the nextcentury as a result of the increasing intensity and frequencyof extreme storms. The distribution of claims is unlikely tobe even as construction quality, property values and insur-ance coverage vary widely worldwide. In response, theinsurance industry could adapt by raising the cost of insur-ance through measures such as increasing premiums,restricting coverage, etc.157 Indeed, the costs of insurancecoverage are expected to increase significantly if infrequentbut catastrophic events become more common in the future.

In addition, the uncertainty surrounding the probabil-ity of high-loss events in the future is likely to place upwardpressure on insurance premiums.158 The implications of thiswill be harshest on low- (and possibly middle-) incomehouseholds in developed countries if they are no longer ableto afford insurance to recover from climate change-relatedevents. It is already the case in the insurance industry thatindividuals tend to be underinsured, especially againstevents with low probabilities of occurrence. Studies have

Climate changecould result inincreasing demandfor insurance whilereducing insurability


Box 4.7 Impacts of climate change upon the insurance industry

• In 1992, Hurricane Andrew hit southern Florida (US) and resulted in over US$45 billion in damage (2005 dollars). In the aftermath, 12insurance companies dissolved.a

• The average annual damage from hurricanes in the US is estimated to increase by US$8 billion (2005 dollars) due to intensification,assuming a scenario in which CO2 levels double.b

• By the 2080s, a severe hurricane season in the US would increase annual insured damage by 75 per cent, while in Japan, insured damagewould increase by 65 per cent.c

• Insured damage in Europe are estimated to increase by 5 per cent as a result of extreme storms, with the costs of a 100-year stormdoubling from US$25 billion to US$50 billion by the 2080s.c

• Miami (US) has over US$900 billion of capital stock at risk from severe coastal storms, and London (UK) has at least US$220 billion ofassets located on a floodplain.d

• The gross regional product of the New York City region (US) is estimated to be nearly US$1 trillion annually and losses from a singlelarge event could be in the range of 0.5 to 25 per cent, or as much as US$250 billion.e

• The full macroeconomic costs of Hurricane Katrina of 2005 are estimated at US$130 billion, while the gross state product for Louisiana(US) in the same year was US$168 billion.f

• In Russia, insurance costs along the Lena River have increased during recent years as a result of more frequent and severe flooding.g

• By 2100, flooding could cause over US$94 billion in property damage in metropolitan Boston (US) if no adaptive actions are taken, withhomeowners on 100-year and 500-year floodplains sustaining an average of US$7000 to US$18,000 in flood damage per household.h

Sources: a Wilbanks et al, 2007, p369; b Nordhaus, 2006; c Hunt and Watkiss, 2007, p21; d Stern, 2006, p14; e Jacob et al, 2000; f Stern, 2006, p11; g Perelet et al, 2007; h Kirshen et al,2006

found that, despite favourable premiums, individuals oftenfail to purchase insurance for low-probability but high-lossevents in part because of the costs associated with finding apolicy.159

Insurance coverage can vary widely within and amongdeveloped and developing countries, as there tends to be acorrelation between economic growth and insurance cover-age.160 While it is expected that insurance coverage willincrease with economic development in many developingcountries, at-risk infrastructure and buildings – includinggovernment-owned properties – compound their vulnerabil-ity by not having insurance coverage.161 As much as 29 percent of total property losses are covered by some form of insurance in developed countries.162 In developingcountries, however, only about 1 per cent of total losses areinsured.163

Private insurers in developed countries will often notprovide insurance or will restrict it in areas that havesuffered significant past losses from floods, which thennecessitates government involvement in order to provideflood insurance.164 The risk of loss then falls upon govern-ment programmes and individual homeowners becauseinsurance out-payments rarely cover the entire cost of recon-struction.165 Furthermore, it would appear that governmentprogrammes are increasingly vulnerable to climate change asa result of an increasing frequency and intensity of extremeclimate events. For example, Hurricane Katrina damage in New Orleans (US) and the surrounding region almostbankrupted the National Flood Insurance Program.166 Popul-ations worldwide are growing within coastal areas andgrowth is expected to increase rapidly, suggesting an inc-rease in the vulnerability of property but also insuranceproviders, including government programmes.167

In some places, the availability of insurance in coastaland other vulnerable areas fails to discourage developmentin areas at risk of flooding from coastal storms.168 In theeastern parts of the Caribbean, for instance, building qualityand location are not typically factored into insurance avail-ability or cost. Due to missing incentives to mitigate theimpacts of extreme climatic events and given that only asmall percentage of the risk is retained by local insurancecompanies, buildings are often ill-prepared targets forextreme weather events or climate change. Instead, insur-ance companies are encouraged by the system to underwriteas many policies as possible, regardless of their sound-ness.169

Ecosystem services

Natural environmental processes provide benefits that arevital to city function and human health. These ecosystemservices include oxygen production, carbon storage, naturalfiltering of toxins and pollutants, and protection of coastalsocieties from flooding and wind during storms. Humanactivities (e.g. development, pollution and wetland destruc-tion) can harm such ecosystem services. Increasingurbanization places greater demand on natural resources andimposes significant changes on the environmental processesthat drive the benefits that societies derive from ecosystemservices.170 Table 4.3 illustrates some of these changes andtheir effects on ecosystem services.

The Millennium Ecosystem Assessment171 indicatesthat climate change has been identified as a key factorbehind the accelerated loss and degradation of ecosystemservices. The assessment found that approximately 60 percent of the ecosystem services evaluated were beingdegraded or used unsustainably.172 Wetland health may beparticularly threatened in the coming decades as thecombined impacts of landscape modification and sea-levelrise cause the Earth’s deltas to sink below oceans levels.173

Loss of ecosystem services, besides potentially affect-ing food provision and human health, can significantlyreduce the revenue of cities. In Durban (South Africa), forexample, the replacement value of the ecosystem services(e.g. water provision, flood prevention) within the city’snetwork of open space was estimated at US$418 million peryear in a study published in 2003.174 This was approximately38 per cent of the city’s total capital and operating budget atthat time, illustrating the financial consequences of losingaccess to these services. A further significant point is that itis the poorest and most vulnerable people/communities whoare most directly reliant on these services in order to meettheir basic needs. They therefore stand to lose the most fromthe damage of ecosystems goods and services underprojected climate change conditions.

Livelihood impacts

Extreme climate events can disrupt the ability of individualsand households in urban areas to sustain livelihoods.175

Climate change-related disasters destroy livelihood assets orthe means of production available to individuals, householdsor groups. These include stocks of natural resources (natural

Populations worldwide aregrowing withincoastal areas …suggesting anincrease in thevulnerability ofproperty but alsoinsurance providers

Climate change hasbeen identified as akey factor behindthe accelerated lossand degradation ofecosystems services


Impact of urbanization Effects on ecosystem Effects on ecosystem service

Reduced permeability of surfaces Reduction of biodiversity Reduced capacity for natural pollutant filtration Surface and groundwater pollutionAlteration of surface and groundwater channels

‘Patchy’ land-use patterns that fragment Reduction of biodiversity Reduction in CO2 retention of nearby land the landscape and spread into natural Loss of trees and soil Reduction in local oxygen supplyenvironments such as forestsExcess emissions of nutrients Mass death of aquatic species Reduction of food sources and other economic activity (e.g. nitrogen, phosphorus), sediments, (e.g. recreation, tourism)metals and other wastes into waterwaysDevelopment on wetlands Loss of wetland area Reduced capacity for natural pollutant filtration

Loss of biodiversity Reduction in local oxygen supplyReduction of natural storm buffer

Table 4.3

Impacts of urbanizationupon ecosystemservices

capital), social relationships (socio-political capital), skillsand health (human capital), infrastructure (physical capital)and financial resources (financial capital), which are neces-sary to sustain a livelihood. By affecting such assets, climatechange-related events can pose a serious threat to urbanlivelihoods.

The effects of climate change on livelihoods will alsodepend on their geographical location and, thus, exposure tothe physical risks associated with climate change. Livelihoodactivities located in low-elevation coastal zones, for instance,will be vulnerable to the impacts of sea-level rise andcyclones. Livelihood impacts will also vary from one contextto another depending on the vulnerability of existing assetsand opportunities. For instance, the livelihoods of the urbanpoor are likely to be most at risk from climate change effectssince their assets and livelihoods are already meagre andunreliable. In particular, individuals living in informal settle-ments are likely to have meagre savings and any disruption totheir livelihood directly affects their ability to buy food andpay bills, including for their children’s education and health-care. Livelihood activities of the urban poor are also moreseverely affected by climate events than other social groupsbecause of their presence in at-risk zones. For instance,flooding makes it difficult for residents of informal settle-ments to conduct small-scale commerce, petty trading andartisan trades, and thus can leave them undernourished fordays while the area and local economy recovers. A one-dayrain event in Maputo (Mozambique) might result in floodsthat linger for three days, and if rains persist, floodwatersmight rise as much as 1m and take a month to recede.176

Where livelihoods are dependent on climate-sensitiveinputs, the impacts of extreme as well as slow-onset climatechanges will be further accentuated. This is so in the case ofagriculture and tourism sectors of the economy. Floodingassociated with sea-level rise has reduced the level oftourism in Venice (Italy), resulting in fewer jobs and econ-omic losses for the city. The city’s productivity is largely tiedto its aquaculture industry and tourism. By 2030, floodingand sea-level rise are projected to cost the city €35 to €42million in decreased tourism levels and €10 to €17 millionin aquaculture revenues.177 Studies have revealed thattourists are unlikely to return to vacation spots in someislands such as Bonaire and Barbados if coral bleaching(which has been linked to warming waters) occurs, resultingin loss of fish and coral species.178

The agricultural sector is also vulnerable to climatevariability; thus, individuals dependent on it for their liveli-hoods are at risk. Low-lying areas in Southeast Asia areparticularly vulnerable to coastal erosion and flooding, whichis likely to result in loss of cultivated land and fisherynurseries. In parts of Africa, livelihoods and national GDP arehighly dependent upon the agricultural sector, whichaccounts for as much as 70 per cent of national GDP in somecountries.179 For urban centres, distant impacts upontourism and agriculture can potentially result in increasedmigration from rural areas, which creates more demand forinfrastructure and services, though this phenomenon is notwell understood.180

PUBLIC HEALTH IMPACTSClimate changes cause local weather conditions – includingextreme heat and severe weather events – that affect publichealth in urban areas. This section describes these keyhealth issues, focusing on impacts related to extremetemperatures, disasters, epidemics, health services andpsychological illnesses. It also considers how poverty acts asa compounding factor which exacerbates the health impactsof climate change.

Climate change can lead to extended periods of heat(i.e. heat waves) and drought. More heat waves have thepotential to increase the incidence of heat stress and heat-related mortality.181 Higher than average night-timetemperatures compound heat stress by eliminating thetypical period during which the human body can recoverfrom heat stress accrued throughout the day.182 In particular,several consecutive nights with temperatures above normalcan negatively impact upon health, leading to heat-relatedillness and mortality.183 For example, the heat wave of 2003across much of Europe is believed to have caused the deathof over 20,000 people. It was the warmest summer since1540 and could become the norm by the end of the 21stcentury.184 Sustained high temperatures in France raisedmortality by an estimated 140 per cent compared to histori-cal averages, while over 2000 excess deaths reportedlyoccurred in England and Wales.185 In the US, high tempera-tures result in an average of 400 deaths and many morehospitalizations each year.186 Projections of climate changeimpacts in New York City (US) further show significantincreases in respiratory-related diseases and hospitaliza-tion.187

With more individuals moving to urban locations,higher temperatures and a rapidly aging society, the threat ofheat-related mortality will become more severe in future.188

Urban residents are especially at a higher risk of heat-relatedmortality as a result of the urban heat-island effect.189

However, death from heat is significantly underreported, aswidely accepted criteria in determining heat-related deathdo not exist. Often, a pre-existing condition is listed as thecause of death, while the role of environmental factors is notconsidered.190

Catastrophic events have both immediate and lastingimpacts upon public health. For example, of 238 naturalcatastrophes occurring from 1950 to 2007, 66 per cent wereclimate related, most of which involved storms or flood-ing.191 Recent flooding in Manila (the Philippines) and surr-ounding areas affected an estimated 1.9 million people andkilled at least 240. Torrential downpours in cities and townsacross north-eastern Brazil in 2010 caused floods thatrendered at least 120,000 people homeless and killed atleast 41 others.192 As the intensity and frequency of precipi-tation increases, ever more urban residents will be at risk ofinjury and property loss.

Increasing intensity of storms and frequency of severestorms threaten to further impact upon urban areas and thehealth of their residents, as illustrated by recent floods inPakistan which killed 1100 people.193 Beyond causingimmediate death and injuries, floods and storms can cause

Extreme climateevents can disruptthe ability of individuals andhouseholds in urbanareas to sustainlivelihoods

Climate changescause local weatherconditions … thataffect public healthin urban areas


long-term damage to facilities that provide health-relatedservices. Power outages can disrupt hospital services, asoccurred in Dresden (Germany) in 2002 when floods fromthe River Elbe affected four out of the six major hospitals inthe region.194 Likewise, clean water provision can becompromised if treatment facilities are structurally damagedor lack power.

Physical climate changes, including temperature,precipitation, humidity and sea-level rise, can alter therange, life cycle and rate of transmission of certain infec-tious diseases. As indicated earlier, flooding can introducecontaminants and diseases into water supplies, which has been linked to increased incidence of diarrhoeal and respiratory illnesses in both developed and developingcountries.195 Psychological illnesses sometimes also inc-rease following storms and other disasters. Post-traumaticstress disorder, anxiety, grief and depression are commonlyobserved among individuals following hurricanes and otherdisasters.196 Declining local air quality is a further conse-quence of climate change which threatens health. Thephotochemical reactions of pollutants in the air which causesmog will intensify as temperatures rise. For example, inLos Angeles, California (US), a 1°C increase in temperaturesabove 22°C results in an increase in the incidence of smogby 5 per cent.197

While the complex relationship of disease incidencewith both environmental and demographic factors makes theidentification of cause–effect relationships difficult, it islikely that climate change will increase the global diseaseburden. The World Health Organization attributes at least150,000 annual deaths to diseases associated with climatechange that has occurred since the 1970s, and estimatesthat death rates from climate-induced disease risk maydouble by 2030.198 Malaria may pose a particular problemfor populations in developing countries, including those insub-Saharan Africa. In contrast, precipitation decreases insome parts of Central America and the Amazon region mayreduce the rate of malaria transmission.199 Climate change isalso likely to affect the transmission of a number of otherdiseases, including dengue fever, rodent-borne diseases anddiarrhoeal illnesses.200

As discussed in a subsequent section of this chapter,diseases can weaken the defences of communities at largeand of certain subgroups of a population in particular (e.g.low-income groups). Health impacts, both immediate andlong term, tend to hit the poorest urban residents the hardestin part because they often lack mobility, resources and insur-ance. These residents also typically occupy the highest-riskareas of cities. These and other distributional impacts arediscussed in the next section of this chapter.

SOCIAL IMPACTSThe degree to which human settlements are vulnerable toclimate change depends not only on the nature and magni-tude of physical changes, but also on the socio-economiccharacteristics of each city. Cities that experience the samecategory of hurricane, for example, may incur very differentmortality levels and economic losses based on relative wealth

and infrastructure. Within cities, too, different populationgroups are differentially affected by the same weather eventsand climatic conditions. Climate change differentiallyimpacts upon groups of individuals, such as marginalizedminorities, women and men, young and old. These impactshave, until recently, received relatively little attentioncompared to other distributional issues.

The distributional effects of climate change in urbanareas within the context of existing vulnerabilities arereviewed below. In doing so, it is critical to acknowledge andconfront compounding vulnerabilities for specific groups inurban areas. Individuals, households and communities whofall into more than one category of vulnerability can find thedeck dramatically stacked against them in terms of theirability to prepare for and respond to the varied impacts thatthey already face and will face in the future. Climate changeimpacts magnify gender and racial inequalities, often affect-ing poor minorities and poor women more than any othergroups. These impacts often exacerbate poverty as individu-als lose their livelihoods and possessions. Sickness andinjury, two of the most important factors attributable toincreasing poverty, affect the poor more than othergroups.201 A vicious cycle then develops whereby marginal-ized groups bear the greatest burdens of climate change,thus preventing them from escaping poverty and leavingthem continuously vulnerable to further change. Urbanplanners and policy-makers are thus often charged withconfronting multiple social issues at once. Understandingthe nature of group-specific climate change dynamics canenable decision-making that seeks to break this cycle – forinstance, by promoting inclusion of typically marginalizedgroups in planning, anticipating the unique needs of groupsduring disasters and preparing accordingly.

Poverty

Climate change is considered a distributional phenomenonbecause it differentially impacts upon individuals and groupsbased on wealth and access to resources. In general, low-income households in both developed and developing coun-tries are most vulnerable to climate change impacts primarilydue to the scale and nature of the assets that they possess orcan draw upon (see Box 4.8). The interactions betweenclimate change and income do not affect developingcountries alone. There are many examples of poor communi-ties in developed countries faring worse than the wealthiergroups during the same disaster. During Hurricane Katrina inNew Orleans (US), residents without cars and financialresources to evacuate were left behind. Some of the hardesthit low-lying neighbourhoods were also the poorest, leavingthose with few resources to bear most of the devastation.202

It has been suggested that the assessment of vulnera-bility to climate change impacts and the ways in which it issocially distributed can perhaps best be understood byconsidering six key questions:203

1 Who lives or works in the locations most exposed tohazards related to the direct or indirect impacts ofclimate change (such as on sites at risk of flooding orlandslides)?

Climate change willincrease the globaldisease burden

Climate changedifferentiallyimpacts upon groupsof individuals, suchas marginalizedminorities, womenand men, young andold


2 Who lives or works in locations lacking the infrastruc-ture that reduces risk (e.g. drains that reduce floodrisk)?

3 Who lacks information, capacity and opportunities totake immediate short-term measures to limit impacts(e.g. to move family and assets before a disaster event)?

4 Whose homes and neighbourhoods face the greatestrisks when impacts occur (e.g. because of poorer qualitybuildings that provide less protection for inhabitantsand their physical assets)?

5 Who is least able to cope with the impacts (includingillness, injury, loss of property and loss of income)?

6 Who is least able to avoid impacts (e.g. by buildingbetter homes, agitating for improved infrastructure ormoving to a safer place)?

A large proportion of the urban population in developingcountries live on sites ill suited to housing – for instance,floodplains or mountain slopes or areas prone to flooding oraffected by seasonal storms, sea surges or other weather-related risks.204 Most such sites are occupied by low-incomehouseholds because other ‘safer’ sites are beyond theirmeans. There is also the growing proportion of the world’surban population living in the low-elevation coastal zone205 –and many studies of particular coastal cities show that mostof those most at risk are low-income groups.206

With regard to who lacks information, capacity andopportunity to take immediate short-term measures to limitimpacts, the devastation caused in so many low-incomesettlements by extreme weather is not necessarily a matterof a lack of knowledge or capacities on the part of theirresidents, although this may be the case for some newarrivals.207 Even if they know of an approaching storm thatmay threaten their homes, the residents of informal settle-ments are often reluctant to move even when advised to doso – for instance, for fear of losing valuables to looters,uncertainty about provisioning for their needs in the placesthey move to and the worry of not being allowed back iftheir house and settlement are damaged. For instance, inSanta Fe (Argentina), large-scale floods affecting large

sections of the population have become common – but manyof those living in informal settlements at high risk fromflooding did not want to move because they had no confi-dence in the police that they would stop looting and wereworried that because they had no legal tenure, they mightnot be allowed back.208

In terms of whose homes and neighbourhoods facegreatest risks when impacts occur, studies of disasterimpacts from extreme weather in urban areas suggest themajority of those who are killed or seriously injured and wholose most or all their assets are from low-income groups.209

Many disasters only affect the inhabitants of particular infor-mal settlements and other slums, and most such disastersare not registered in national or international records ofdisasters.210 The reasons why most of the inhabitants ofinformal settlements are so much at risk is obvious: poor-quality housing with inadequate foundations, high levels ofovercrowding, lack of infrastructure, etc. Most low-incomegroups live in housing without air conditioning or adequateinsulation, and during heat waves, the very young, olderpersons and people in poor health are particularly at risk.211

For instance, in regard to urban centres in India:

[T]he urban residents most vulnerable toclimate change are the poor slum and squattersettlement dwellers and … they are multiplychallenged by even small events that impacttheir livelihoods, income, property, assets andsometimes their lives. Because of systematicexclusion from the formal economy of the city –basic services and entitlements and the impossi-bly high entry barrier into legal land andhousing markets – most poor people live inhazardous sites and are exposed to multipleenvironmental health risks via poor sanitationand water supply, little or no drainage and solidwaste services, air and water pollution and therecurrent threat of being evicted.212

Financial shocks from damage lasts months, even years, aftera disaster occurs. Thus, the extent to which the populationof a given city is protected by insurance will in large partdetermine the impact of disasters. Access to insurance isgenerally more inclusive in cities in developed countriescompared to those in developing countries, where poorhouseholds typically lack access altogether.213 Still, low-income households in developed countries can be excludedfrom insurance where public coverage is inadequate and thecosts of private insurance are prohibitively high. Unlike theirwealthy counterparts, low-income households often lack theresources to mitigate damages after they occur – forinstance, through healthcare, structural repair, communica-tion, food and water.214 In the absence of adequate recoveryassistance, the poor often sacrifice nutrition, children’seducation or any remaining assets to meet their basic needs,thereby further limiting their chance of recovery and escapefrom poverty.215

Evidently, climate change disproportionately affectslower-income groups in both developed and developing

The urban residentsmost vulnerable toclimate change arethe poor slum andsquatter settlementdwellers

Access to insuranceis generally moreinclusive in cities indeveloped countriescompared to thosein developingcountries


Box 4.8 Poverty and climate change impacts in cities

Within any urban centre, it is common for poorer groups to be disproportionately at risk for avariety of reasons, including:

• greater exposure to hazards (e.g. through living on floodplains or unstable slopes);a

• lack of risk-reducing housing and infrastructure (e.g. poor-quality housing, lack of drainagesystems);

• less adaptive capacity (e.g. lacking the income or assets that allow a move to better qualityhousing or less dangerous sites);

• less state provision for assistance in the event of a disaster (e.g. needed emergencyresponses and support for rebuilding or repairing homes and livelihoods; indeed, stateaction may increase exposure to hazards by limiting access to safe sites for housing);b and

• less legal and financial protection (e.g. a lack of legal tenure for housing sites; lack of insur-ance and disaster-proof assets).c

Sources: a Ruth and Ibarrarán, 2009, p56; b Syukrizal et al, 2009; c Bartlett et al, 2009; Hardoy and Pandiella, 2009

countries. Although these distributional impacts are far frombeing adequately addressed on international or nationallevels, the nexus between poverty and climate change hassteadily worked its way into the climate change discourse,emerging in focus groups, meetings and reports by manyinternational organizations, including the Organisation forEconomic Co-operation and Development (OECD) and theWorld Bank.216

Gender

In most urban centres, there are significant differencesbetween women and men in terms of their exposure toclimate-related hazards, and their capacity to avoid, copewith or adapt to them.217 This is because men and womendiffer in their livelihoods, familial roles, production andconsumption patterns and other behaviours, perceptions ofrisk, and are in some cases treated differently with respect toplanning and relief efforts during and after disasters (seeTable 4.4).

In general, women, especially poor women, are morelikely than men to suffer injuries or death when a naturaldisaster occurs, with more severe disasters correlating withwider gaps in relative risk. Poor women have been found tobe more exposed to direct harm from flooding or hurricanescompared to other socio-economic groups.218 In 1991, acyclone in Bangladesh killed five times as many females asmales.219 Females comprised more than three-quarters ofthe deaths in four Indonesian villages hit by the 2005tsunami, while in the village of Kuala Cangkoy, where theworst devastation occurred, females accounted for 80 percent of the deaths.220 Gendered impacts are evident in richcountries as well, particularly in poor communities. Forexample, in the French heat wave of 2003, about 70 percent of fatalities were women, although this number may beartificially high since there are more women than men inolder age groups.221

To some extent, the higher death rates for women indisasters can be explained by the fact that women comprisethe majority of the world’s poor population, who face vulner-ability factors as previously discussed. This statistic,

however, can obscure the many other important factors thatplace women at greater risk than men. In developingcountries, women often experience unequal access toresources, credit, insurance, services and information.Women’s socio-cultural roles and typical care-giving responsi-bilities often prevent them from migrating and seekingshelter before and after disaster events. In some cases,women may not be allowed to travel alone and may beprevented from learning skills that could aid their survivalduring a disaster. Also, women’s lower economic statusincreases their vulnerability in the event of a disaster occur-ring. When homes are destroyed or damaged, this oftenaffects women’s incomes more than men’s as they oftenengage in income-generating activities from home and there-fore lose income when homes are destroyed.222 Whereaccess to resources and the social status of women are nearlyequal to that of men, the mortality difference between thesexes is much smaller or, in fact, negligible, compared tosocieties with wide gender inequalities.223

The method by which aid is distributed followingdisasters further contributes to gendered vulnerability. Inboth developing and developed countries, women may havelimited capacity to secure relief aid, whether due to formalassistance policies or cultural norms.224 In Bangladesh, forexample, women have traditionally had difficulty receivingrelief aid after disasters because it was difficult for them towait in long lines at recovery centres when they needed tocare for children at home. Expanded recovery systems thatprovide door-to-door service are helping to address thisissue.225

Households that are headed by women do not alwaysreceive the assistance they need when disaster relief istailored to reintegrate men into the workforce or when itprivileges male-headed households for relief aid.226 Forexample, relief checks following Hurricane Andrew in Miami(US) were distributed to men as traditional heads of house-hold, ignoring the reality that many families were thenheaded by women.227 If men leave their families, asfrequently occurs following a natural disaster, women arerendered ineligible for public assistance or may go unrecog-nized by the system.

Women, especiallypoor women, aremore likely thanmen to sufferinjuries or deathwhen a naturaldisaster occurs

Women’s lowereconomic statusincreases theirvulnerability in theevent of a disasteroccurring


Aspect of vulnerability Contribution to urban vulnerability Contribution to climate vulnerability

Gendered division of labour and Women have prime responsibility for ‘reproductive’ Limited financial assets to build resilience and to cope ‘poverty of time’ labour; lack of time to engage in ‘productive’ labour with disaster events Gender-ascribed social responsibilities Women have prime responsibility for ‘reproductive’ Additional domestic responsibilities when access to food,

labour; lack of time to engage in ‘productive’ labour water and sanitation are disrupted; additional time required to care for young, sick and elderly

Cultural expectations of gender norms Constraints on women’s mobility and involvement Higher mortality from disaster events due to lack of in certain activities skills and knowledge

Unequal entitlements to land and Limited access to productive resources Limited ability to invest in more resilient land or shelter propertyHigher representation of women Lower wages and lack of financial security Damage to homes and neighbourhoods affects women’s in informal sectors incomes more severely as income-earning activities are

often undertaken at home Safety and security in public spaces Limited freedom to use public space Particular problem in temporary accommodation/

relocation sites; high rates of sexual abuse and violence Limited engagement of women in Urban plans fail to meet particular needs of Climate adaptation plans fail to meet needs of women planning processes women and children and children; failure to incorporate women’s perspectives

may result in higher levels of risk being accepted

Source: IFRC, 2010

Table 4.4

Gender and climatevulnerability

Likewise, trauma programmes are often not tailoredto the specific, and, at times, unique needs of men andwomen. In the aftermath of storms, women often dispropor-tionately experience sexual or domestic violence.228 Disasterrelief programmes are sometimes inadequate to meet themedical needs of women, especially those related to repro-ductive and psychological health. Women were 2.7 timesmore likely than men to exhibit clinical symptoms of post-traumatic stress disorder following Hurricane Katrina, andmany went untreated for years after the event because oflimited access to public assistance programmes and lack ofhealth insurance.229 In some cases, men may take greaterrisks following natural disasters and may not receive treat-ment for trauma because of gender roles and stereotypes.230

The psychological needs of men may also be overlooked indisaster programmes; for example, men were not offeredcounselling following flooding of the Koshi River in 2008that affected Bihar, India and Nepal.231

Restrictions on women’s livelihood also increase theirvulnerability to climate change in both developing and devel-oped countries. Women sometimes have less access toeducation compared to men and tend to earn lower wagesthan men as well, especially in developing countries (evenfor the same work). Similarly, in developed countries, genderdifferences in employment opportunities and pay are one ofthe greatest contributors to increased poverty rates amongwomen.232 In many developing countries, marriage customsmay prevent women from working at all outside the home,and may remove women from social networks and extendedfamily.233 Women’s ability to contribute to their own welfareand garner resources and investments that could help themrecover from disasters is thus limited.

Furthermore, women are often excluded fromplanning processes and discussions about climate change. Asa result, the perspectives and needs of women are insuffi-ciently incorporated within processes and mechanisms toaddress climate change, if they are included at all. There islittle evidence of specific efforts to target women in adapta-tion activities funded by bilateral and multilateral prog-rammes. In excluding them from planning processes, anopportunity is missed to gain the unique knowledge thatwomen possess regarding mitigation strategies, naturalresource use, and adaptation and coping strategies followingdisasters. For instance, as primary caregivers, women couldprovide vital information about storing and protecting foodand valuables during a disaster, educating children aboutsurvival strategies, and reinforcing structures before andafter a severe weather event.234

Age

Young children are particularly vulnerable to climate changeimpacts, in part because of their physiological immaturity(see Box 4.9). Due to their limited cognitive ability andbehavioural experiences compared to adults, children areless equipped to handle disaster risks. They are more suscep-tible to diarrhoeal diseases and malaria – which, as men-tioned earlier, are anticipated to increase with climatechange in many regions. Furthermore, physical health

damage can be more severe and long lasting in children thanadults because their bodies and organs are still develop-ing,235 and higher metabolism in children makes their needfor constant sustenance more pressing than it is for adults.Food and water scarcity thus has particularly rapid andserious consequences for children living in poverty.236

Children have limited ability to care for their basicneeds and take actions to adjust their physical conditions tocope with external conditions. Adults are responsible forthese and other needs of children, including providing infor-mation. In the absence of adult support, these and otherissues – including reduced ability to communicate effectivelyand highly restricted mobility – leave children especiallyvulnerable to climate change impacts.

For some children in some places, the addedchallenges brought by climate change (including higher risksfrom under-nutrition, intestinal parasites, diarrhoealdiseases or malaria) could erode their opportunities for lear-ning and growth – for instance, through lower cognitive capa-city and performance. Learning is also dependent onsupportive social and physical environments and the oppor-tunities to master new skills. Disasters often result in theinterruption of formal schooling for months at a time, andchildren are more likely to be withdrawn from school whenhouseholds face shocks.

Levels of psychological vulnerability and resiliencedepend on children’s health and internal strengths, as wellas household dynamics and levels of social support. Povertyand social status can have an important role in this regard.The losses, hardships and uncertainties surrounding stress-ful events can have high costs for children. Increased levelsof irritability, withdrawal and family conflict are not unusualafter disasters. High stress for adults can have serious impli-cations for children, contributing to higher levels of neglect.Increased rates of child abuse have long been associatedwith such factors as parental depression, increased poverty,loss of property or a breakdown in social support.

Displacement and life in emergency or transitionalhousing after disasters or evictions have been noted in manycontexts to lead to an erosion of the social controls thatnormally regulate behaviour within households and commu-nities. Overcrowding, chaotic conditions, lack of privacy andthe collapse of regular routines can contribute to anger,frustration and violence. Adolescent girls especially reportsexual harassment and abuse. The synergistic and cumula-tive effects of such physical and social stressors can affectchildren’s development on all fronts. As the numbers ofdisplaced people grow, these dysfunctional environments arelikely to become the setting within which more and morechildren spend their early years.

Even less extreme events can create havoc in families’lives, deepening the level of poverty. When times are hard,children can become an asset that is drawn on to maintainthe stability of the household. Children may be pulled fromschool to work or take care of siblings. Some children may beconsidered more ‘expendable’ than others. Many of theyoung prostitutes in Bombay (India) are from poor ruralvillages in Nepal, where inadequate crop yields lead familiesto sacrifice one child so that others may survive.

Women are oftenexcluded fromplanning processesand discussionsabout climatechange

Young children areparticularly vulnerable toclimate changeimpacts, in partbecause of theirphysiologicalimmaturity


Older persons share similar physical and social vulner-abilities with children. Pre-existing illnesses and physicalailments limit their mobility and coping capacity, which mayprevent them from evacuating or seeking shelter inemergency situations. Since their bodies adjust more slowlyto physical conditions than younger populations, they maynot perceive excessive heat quickly enough to prevent heatstroke. Empirical evidence indicates that the elderly displaydisproportionately higher injury rates after natural disastersand higher rates of heat wave mortality.237 A recent study onclimate change impacts in Oceania found that 1100 peopleaged over 65 die each year in ten Australian and two NewZealand cities as a result of heat waves.238

While adaptive measures do exist to help the elderlycombat their physical vulnerability, these mechanisms areoften solely accessible to wealthy populations. The elderlyare more likely than younger people to require assisted trans-portation out of a dangerous situation; but poor individualsmay not be able to afford private transportation. Lack of

personal contacts and distrust of strangers decreases theiraccess to volunteered assistance, and they are also less likelyto accept financial assistance from public recovery and aidprogrammes.239

The vulnerability of the elderly is, thus, like othergroups, dependent upon their economic status. Yet, all elsebeing equal, the elderly show disproportionate rates ofpoverty, for the most part because they no longer maintain asource of income and tend to have low endowments ofassets.240 While rates and magnitude of poverty are greaterin developing countries, poor older persons in developedcountries are more likely to live alone and be sociallyisolated.

Ethnic and other minorities (includingindigenous groups)

Racial and ethnic minorities also exhibit increased vulnera-bilities to climate change in both developed and developing

The elderly displaydisproportionatelyhigher injury ratesafter natural disasters and higherrates of heat wavemortality


Box 4.9 Climate change risks for children

Drawing on studies on children and their vulnerabilities, it is possible to highlight the following risks associated with climate change that haveclear impacts upon child health and survival:

• Mortality in extreme events: in most developing countries, the loss of life is disproportionately high among children – especially among thepoor – during such extreme events as flooding, high winds and landslides. Children are 14 to 44 per cent more likely to die due toenvironmental variables, including extremes in temperature, flooding and severe weather events, than the total population at large.a Forexample, drowning incidents in floods are particularly high for children in Kampala (Uganda).b A study of flood-related mortalities inNepal found that the death rate for children aged two to nine was more than double that of adults; and pre-school girls were five timesmore likely to die than adult men.c The average death rate for children was twice that of adults in flooding in Nepal, with poor childrensuffering the highest death rates.d

• Water and sanitation-related illnesses: children under five are the main victims (80 per cent globally) of sanitation-related illnesses (primarilydiarrhoeal diseases)e because of their less developed immunity systems and because their behaviour can bring them into contact withpathogens. This also results in higher levels of malnutrition and increased vulnerability to other illnesses. Droughts, heavy or prolongedrains, flooding and conditions after disasters – as well as climate change-related constraints on freshwater supplies in many urban centres– all intensify the risks, which are already very high in informal settlements or other areas with concentrations of low-income groups.

• Malaria, dengue and other tropical diseases: warmer average temperatures are expanding the areas where many tropical diseases can occur,with children most often the victims. In many locations, the most threatening tropical disease is malaria. Up to 50 per cent of the world’spopulation is now considered to be at risk. In Africa, 65 per cent of mortality is among children under five.f Malaria also increases theseverity of other diseases, more than doubling overall mortality for young children. Climate change is also accelerating the comeback ofdengue fever in many countries in the Americas.g

• Heat stress: young children, along with older persons, are at highest risk from heat stress. Research in São Paulo (Brazil) found that forevery degree increase above 20°C, there was a 2.6 per cent increase in overall mortality in children under 15 (same as for those over65).h Risks for younger children are higher. Those in poor urban areas may be at highest risk because of the urban heat-island effect, highlevels of congestion and little open space and vegetation.i

• Malnutrition: malnutrition results from food shortages (e.g. as a result of reduced rainfall, other changes affecting agriculture, or interrup-tions in supplies during sudden acute events) and is also closely tied to unsanitary conditions and to children’s general state of health. Ifchildren are already undernourished, they are less likely to withstand the stress of an extreme event. Malnutrition increases children’svulnerability on every front and can result in long-term physical and mental stunting.

• Injury: after extreme events, injury rates go up. Children, because of their size and developmental immaturity, are particularly susceptibleand are more likely to experience serious and long-term effects (from burns, broken bones, head injuries, etc.) because of their size andphysiological immaturity.j

• Quality of care: as conditions become more challenging to health, so do the burdens faced by caregivers. These problems are seldom facedone at a time – risk factors generally exist in clusters. Overstretched and exhausted caregivers are more likely to leave children unsuper-vised and to cut corners in all the chores that are necessary for healthy living.

Sources: a Bartlett, 2008; b Mabasi, 2009, p5; c Pradhan et al, 2007; d UN, 2007; e Murray and Lopez, 1996; f Breman et al, 2004; g World Bank, 2009c; h Gouveia et al, 2003; i Kovats andAkhtar, 2008; j Berger and Mohan, 1996

countries. Discriminatory practices often segregate groupsof minorities into the highest-risk neighbourhoods, usuallywithout access to insurance and loans as security againstclimate change impacts. The majority of flooding victims inBihar (India) in 2007 were ‘untouchable’ low-caste groupswho resided in floodplains and areas prone to landslides.241

The most vulnerable low-lying communities in New Orleans(US) are comprised mostly of African-Americans. This groupsuffered the relatively most severe losses of life and assetsduring Hurricane Katrina.242

In both developed and developing countries, provi-sion of government assistance following disasters is oftenless accessible to racial and ethnic minorities. Aid workersmay not be properly educated regarding cultural norms, orimportant information regarding assistance may not be avail-able in the right language.243 Since aid is sometimesstructured around the household as a single family unit,some ethnic minorities may not receive as much assistanceas majority groups. For instance, in the US, the FederalEmergency Management Agency’s assistance to Haitianresidents of Florida following tropical storm damage hasbeen found to be insufficient because several families tendto occupy a single household.244 Outright exclusion ofcertain groups from disaster relief occurred during recentdisasters in South Asia, including during the flooding of theKoshi River in 2008 in Bihar, India and Nepal, the 2005Kashmir earthquake and the 2004 Indian Ocean tsunami.Assessments of the relief and reconstruction efforts follow-ing these disasters have revealed discriminatory practicesand human rights abuses against women, the poor, indige-nous groups and the disabled.245 Furthermore, the know-ledge of government views towards minority groups or previ-ous examples of discrimination in some cases discouragesminorities from seeking assistance.246

Similarly, indigenous peoples in many areas havehistorically faced factors that can increase their relativevulnerability. Alienation from decision-making, education,healthcare and information regarding assistance and reliefprogrammes are common among indigenous peoples.Moreover, indigenous peoples often lack security of landtenure and legally recognized property rights, which canforce them to settle in hazardous areas if they are removedfrom their land.247 Lack of legal property can also limit theability of indigenous peoples to adapt to climate change,particularly when, for example, their adaptation strategiesinvolve seasonal migration due to drought. If their traditionalmeans of adapting are restricted by denial to move into newareas, they may not be able to cope with changing climaticconditions.248

DISPLACEMENT ANDFORCED MIGRATIONMillions of people move each year, with over 5 million cross-ing international borders into developed countries and evengreater numbers moving into or within developingcountries.249 The reasons why people move are complex andinterrelated, and there is evidence that poor environmental

conditions can contribute to the decision of groups orindividuals to move. As the world’s climate changes, result-ing environmental degradation, drought and sea-level risemay lead to the permanent displacement of people and,consequently, increased internal and international migra-tion. The term migrant does not imply that movement wasforced, but refers to a person who has changed place ofresidence either by moving across international borders(international migrant) or moving within one’s country oforigin (internal migrant).250 This section describes theobserved role of the environment in migration, projectionsfor future migration as a result of climate change, and theconsequences of migration.

Migration has been documented around the worldboth as a response to sudden-onset natural disasters andslow-onset changing environmental conditions. In 2008, anestimated 20 million individuals were displaced due tosudden-onset natural disasters alone.251 Flooding and severestorms have been linked to migration in the Philippines,Pakistan, China and the Democratic People’s Republic ofKorea.252 Decades of drought and land degradation havecontributed to the relocation of nearly 8 million inhabitantsof north-eastern Brazil to the central and southern regions ofthe country since the 1960s.253 In Ghana, studies havefound evidence of drought-induced internal migration fromnorth-western to central and southern regions. NorthernGhanaians relocate to Ghana’s middle regions because of thecombination of poor agro-ecological conditions at home andeasy access to fertile lands in the more humid south. Assuch, 30.8 per cent of people born in north-western Ghananow live elsewhere.254

Still, figures for environment-related migration arecontentious because it is difficult to ascribe a single cause tomost migration events. Evaluation of historical migrationevents, both permanent and temporary, suggests thatenvironmental decline can serve as an important ‘push’factor in generating movement; but it is not typically the solecausative agent of migration. As a further complicating issue,environmental degradation itself may occur not only due toclimate change impacts, but as a side effect of war, politicalinstability, overpopulation or widespread poverty. Changingenvironmental conditions may exacerbate longstandingproblems such as conflict or food shortages. Many factorsthat can be implicated in migration are difficult to entangle,and it is impossible to ascribe blame to a single startingfactor.

The response of any particular community to environ-mental change depends on a variety of socio-economic andhistorical considerations. In the least developed countrieswhere rural economic activities are disrupted by environ-mental conditions (e.g. drought), migration is usuallytemporary and internal.255 If societies are able to adapt toslow-onset changes, they may only migrate seasonally orindividuals may leave temporarily and send back resources totheir remaining family. While sudden disasters often forcepeople to move quickly to a safe location, the poor do notoften have the resources to move, and loss of resourcesduring disasters may only make it less likely that low-incomehouseholds will eventually relocate.256


Racial and ethnicminorities alsoexhibit increasedvulnerabilities toclimate change inboth developed anddeveloping countries

As the world’sclimate changes,resultingenvironmental degradation, droughtand sea-level risemay lead to …increased internaland internationalmigration

Projections for future climate change-related displace-ment average 200 million migrants by 2050; yet estimatesdepend greatly on the degree of climate change and howabruptly change occurs.257 Despite difficulties in predictingglobal migration patterns, there are areas that may be partic-ularly affected because of their vulnerability to risk factors.Populations located at low elevations are vulnerable toclimate-induced migration, especially in areas where othervulnerability factors exist (e.g. overcrowding). Small islandstates, including the Bahamas, Marshall Islands and Kiribati,are located entirely below 3m or 4m above sea level, so theirpopulations here may have to relocate entirely as sea-levelrise and coastal subsidence continue.258

It is difficult to establish where displaced residentsare likely to relocate to. In most historical cases, displacedresidents move to other regions of their native country. Ruralto urban migration has been a major component of urbaniza-tion across Africa and in Asia, though it should not be anassumed response to environmental degradation around theworld. In regions with strong agriculture sectors, migrantsmay move from one rural area to another rather than fromrural areas to cities. In rapidly urbanizing countries (e.g. incountries throughout the Latin American and Caribbeanregion), migration from one city to another is common. Ruralto urban migration typically happens where economicgrowth is occurring or there is an expansive manufacturingor service economy.259 However, it is also reasonable toexpect that some international migration may occur whereinland relocation is impossible or where cultural and historicrelationships exist between countries.

Depending on the scale and nature of these events,migration can result in social disruption or conflict,especially if migratory events bring into contact peoples withpre-existing social or cultural tensions. New arrivals to citiesmay also be seen as competition for jobs or resources, gener-ating distrust and possibly leading to conflict. Socialdisruption is particularly likely in developing countrieswhere cities may be less able to absorb new residents. Inaddition, political instability common to many developingcountries can at best fail to mitigate conflicts and can, atworst, facilitate them.260

Forced migrants can also find themselves vulnerableto a range of risks, climate related and otherwise. They oftenface threats to their health and personal security and, insome areas of the world, are at danger of human traffickingand sexual exploitation.261 The nature and magnitude ofthese implications will depend on the location of events,number of people involved, and the time-scale over whichmigration occurs and preparations have been made.

A growing body of evidence suggests that threats tolivelihoods, immigration and resource scarcity can becomesources of violent conflict, and indicates that climate changecan directly and indirectly influence these trends.262 Indeed,the United Nations Security Council acknowledges climatechange as a threat to human security as resource scarcity,water stress and migration potentially lead to competitionand conflict.263 Still, there is much uncertainty about thespecific causal links between climate change, human insecu-rity and the risk of violent conflict. More research regarding

conflict, especially at the regional level, would be useful inidentifying where policy intervention may be necessary nowand in future.264

IDENTIFYING CITIESVULNERABLE TO CLIMATE CHANGEThe concept of vulnerability in relation to climate change isalso applicable to larger systems such as cities or city-regionsor to resources and ecosystem services. This section of thechapter describes the key indicators of vulnerability in urbanareas with regard to risk of exposure and adaptive capacity.Cities may not only serve as sources of particular vulnerabil-ity to climate change, but also as centres of concentration forresources, novel ideas and capacity for technological innova-tion. In this sense, although cities face interacting riskfactors from climate change, they may have the ability torespond to climate change while providing tools and lessonsfor others.

Urbanization

As indicated in Chapter 1, levels of urbanization are increas-ing worldwide. Population growth in urban centres has thepotential to significantly exacerbate climate change impacts.Increasing population means greater demand for resources –including energy, food and water – and greater volumes ofwaste products. Thus, for those regions of the world whereresource scarcity is an existing problem, urbanization can bea significant vulnerability factor. Population growth can alsocause stronger urban heat-island impacts, which can be aparticular challenge for small compact cities such as thosetypical of Southern Europe.

Where population growth occurs rapidly, demand forhousing, infrastructure and services can grow much fasterthan supply. This can force development in hazardous areasor with inadequate construction materials and techniques.In many cases in developing countries, urban slum expansionresults in part because population growth outpaces theconstruction of adequate affordable housing. Unplannedpopulation growth can also result in sprawling urban settle-ments that encroach upon natural flood and storm buffers.

Rates of urbanization are higher in developingcountries, which are less prepared than developed countriesto deal with the resulting impacts. For these regions of theworld, population growth can act as an acute threat multiplier,concentrating residents in high-risk areas without infrastruc-ture or services, and accelerating environmental degradation.As cities continue to rapidly urbanize surrounding areas, theytypically increase their exposure to climate events as develop-ment patterns expand into areas that are more vulnerable toclimate change and extreme climatic events.265

Urban areas face a dichotomy with regard to theirvulnerability and resilience to climate change. On the onehand, larger cities are more likely than other regions to beaffected by climate events because of their larger size andpopulations.266 On the other hand, larger cities tend to have

Projections forfuture climatechange-relateddisplacementaverage 200 millionmigrants by 2050

Population growthin urban centres hasthe potential tosignificantly exacerbate climatechange impacts


a significant accumulation of human and financial capitalthat allows them to plan and respond more effectively toextreme events, as cities can draw on talents and financialresources from around the world to aid in rescue and recov-ery.267 Also, adaptation can be expensive and, as a result,larger cities tend to be better protected, both by engineeringworks and early warning systems.268 However, this general-ization does not necessarily hold true in developing cities,where prevalence of slums, inadequate governance andlimited resources can reduce resilience.269

Despite the inherent issues associated with growingurban populations, most problems can be mitigated withurban planning that diverts growth away from highlyhazardous areas, enforces energy and water efficiencystandards for buildings, and minimizes urban heat effects.Thus, the extent to which urbanization acts as an additionalsource of vulnerability often depends on the integration offuture population projections within land-use and infrastruc-ture planning at the city level.

Economic development

Climate change impacts are not experienced in the same wayby cities in developing and developed countries. Risk isskewed towards developing countries such that more peopleare at risk of being affected by a natural disaster in a develop-ing country compared to a similar disaster in a developedcountry.270 Lack of economic strength, as is the case in manydeveloping country cities, exacerbates vulnerability by limit-ing the ability to minimize and adapt to the impacts ofclimate-related hazards. Studies have linked the size of acity’s coastal population and economy (e.g. GDP and GDPper capita) to its vulnerability to sea-level rise.271 Otherissues underlying the risk differential between cities indeveloping and developed countries include the integrity ofinfrastructure and urban planning, or lack thereof; the avail-ability of resources and information; levels of risk awareness;presence of disease and malnourishment; and dependenceon natural resources.

Developing country cities often lack risk managementplans, early warning systems and the ability or foresight tomove residents to safer locations when disasters areinevitable. Their local authorities do not have the capacity torespond to natural disasters, and if laws or plans do exist fordisaster response, they are rendered ineffective from lack ofhuman or financial capital to enact them. For instance, thecapacity of local authorities in developing countries tominimize the effects of flooding is restricted compared todeveloped countries, including through physical protectionsuch as complex and modern water treatment and catch-ment systems, flood barriers and other risk buffers.Moreover, due to the unequal distribution or general lack ofresources, political instability and corruption, many develop-ing country cities lack the network of governmental andnon-governmental institutions that aid recovery efforts inwealthier countries.272 As a result, developing countries canexperience great physical damage during flooding or severeweather events and often have difficulty rebuilding theirinfrastructure and economy. Furthermore, a recent study

concludes that the National Adaptation Programmes ofAction (NAPAs) which are intended to guide adaptationresponses in least developed countries and small islandstates are inadequate to protect public health from climatechange impacts.273

The diversity of local sources of income is a furtherimportant facet of the magnitude of climate change impactsin cities. Where cities are reliant upon few industries for themajority of local economic productivity, they can be seriouslyaffected if those activities are affected by climate changeboth due to short-term monetary losses and longer-termeconomic decline. In those areas with low economic diver-sity, loss of a single industry leaves few other options forworkers who lose their jobs. In Venice (Italy), for example,flood impacts on tourism and aquaculture leave the city’sfuture uncertain.

An additional vulnerability factor for cities is thedegree of disparity between high- and low-income groups. Inboth developing and developed country cities, the poorestare typically the hardest hit by natural disasters and leastable to cope with a range of climate change impacts. Thosecities with great income inequality and large populations ofresidents living in poverty have inherently high vulnerability.

Some developing country cities may be unable toprepare for climate change or to cope with climate changebecause they are hampered by outbreaks of disease orchronic malnourishment. Unhealthy populations havereduced mobility and may be especially sensitive to waterand food shortages. Prevalence of HIV (human immunodefi-ciency virus) and AIDS (acquired immune deficiencysyndrome), for example, have been cited among the primaryreasons that the population of Malawi has been increasinglyvulnerable to the effects of regional drought.274 The impactsof disease do not end with infected individuals, but ratherweaken the defences of entire communities. As a greaterproportion of the population becomes sick, food andeconomic productivity declines and contributes to higherrates of poverty and malnourishment.275 It is clear thatsimilar effects could occur not only in regions with AIDSepidemics, but those experiencing outbreaks of plague, fluand other infectious disease.

Physical exposure

The level of vulnerability of an urban area to climate changerisks depends, in part, on how much of the city’s populationand economic assets are located in high-risk areas (i.e.exposure). In many cases, exposure level will be a functionof the location of the city itself. Many of the world’s largestcities are located in areas vulnerable to climate events, suchas low-lying coastal areas. Though low-elevation coastalzones account for only 2 per cent of the world’s total landarea, this area accounts for approximately 13 per cent of theworld’s urban population.276 Coastal cities in this zone havehigh levels of exposure – both of population and assets – tosea-level rise, storm surges and flooding simply as a functionof being so near the ocean.

Exposure can also be linked to land-use planningwithin the city, including continued development in known

Climate changeimpacts are notexperienced in thesame way by citiesin developing anddeveloped countries

The level of vulnerability of anurban area toclimate change risksdepends … on howmuch of the city’spopulation andeconomic assets arelocated in high-riskareas


hazardous zones, and the destruction of natural protectiveareas.277 Coastal communities who encroach onto wetlands,sand dunes and forested areas increase the likelihood offlooding, together with all its associated impacts uponhousing structures, transportation networks and waterquality.278

Weak structural defence mechanisms and oversight ofbuilding codes further increase the vulnerability of cities inhigh-risk areas. Sea walls, levees, dykes and water pumps canreduce the chances and intensity of flooding from stormsurges and heavy precipitation, while reinforcements onhousing and transportation systems can limit damage whenflooding does occur. Those cities with inadequate, agingstructural defences and infrastructure in need of repairs orupgrades are often highly vulnerable to climate change risks.The system of structural defences throughout cities in Japan,for example, has resulted in fewer cyclone damages than incities in the Philippines, even though exposure risk in Japanis generally higher.279

In particular, the physical infrastructure of slumsincreases the vulnerability of residents to climate changeimpacts. In 2010, nearly 32.7 per cent of the urban popula-tion in developing countries lived in slums,280 which areespecially vulnerable to climate change. The very definingcharacteristics of slums – namely, structures of substandardquality, lack of basic services, overcrowding and social exclusion – clearly suggest that residents are particularlyvulnerable to climate change impacts.281 Disaster risk isoften high for slums because construction occurs in particu-larly hazardous areas, including steep slopes or in flood-plains. In Nairobi (Kenya), for example, poor urban planninghas resulted in residential and commercial development infloodplains that restricts water flow and increases the likeli-hood of flooding.282 The lack of adequate drainage systemsleaves such settlements open to rapid flash floods, as in thecase of those that occurred near Caracas (Venezuela) in1999 and Mumbai (India) in July 2005.283 In Mozambique,politicized land distribution systems and high pricing forcesurban residents to live in unregulated slums and informalsettlements with inadequate drainage. As a result, severeflooding in 2000 disproportionately affected the urban poorliving in a number of urban locations.284 Box 4.10 furtherillustrates the challenge of flooding in the slums of Kampala(Uganda).

Urban governance and planning

The ability of urban centres to prepare for and respond toclimate change is linked in large part to the quality of localgovernance and the strength of the institutional networksavailable to provide assistance to residents, as elaboratedupon in greater detail in Chapters 5 and 6. Urban gover-nance and planning can improve resilience to climate changeimpacts through targeted financing of adaptation, broadinstitutional strengthening and minimizing the drivers ofvulnerability.285 Urban areas with weak governance systems– as a result of political instability, exclusion of climatechange from the political agenda or lack of governmentalresources – are highly vulnerable to climate change impacts.

In many cities throughout developing countries, populationscontinue to grow in the absence of effective urban planning,resulting in living conditions that exacerbate climate changeimpacts, and development in vulnerable areas such as coastalzones at risk from sea-level rise, flooding and coastal storms.Similarly, weak building codes and standards (or lack ofenforcement) increase the vulnerability of individual house-holds and entire communities.286

Civil society institutions – including community-basedorganizations, NGOs, faith-based organizations and organiza-tions for minorities and women – can mitigate vulnerabilityby helping populations cope with and adapt to change. Thesemay be especially powerful resources for underrepresentedminorities, women and indigenous peoples whose uniqueneeds are often overlooked even where climate change is afocus of political institutions. Cities where these resourcesare unavailable or discouraged may be particularly vulnerableto change.

Disaster preparedness

Natural and human-made disasters have been on the riseworldwide since the 1950s, coinciding with the rise in worldurban population (see Figure 4.2).287 As climate changecontinues to occur, disasters such as landslides, floods,windstorms and extreme temperatures may occur withgreater frequency and intensity. Urban vulnerability toclimate change will therefore depend upon disaster prepared-ness, defined by the International Strategy for DisasterReduction Secretariat as ‘activities and measures taken inadvance to ensure effective response to the impact ofhazards, including the issuance of timely and effective earlywarnings and the temporary evacuation of people andproperty from threatened locations’.288

Disaster preparedness may be linked to governance

The physical infrastructure ofslums increases thevulnerability ofresidents to climatechange impacts


Box 4.10 Vulnerability of slums to climate change: The case of Kampala, Uganda

Kampala, the capital city of Uganda, has been experiencing rapid urbanization and slum expan-sion. Currently, over 50 per cent of the urban population live in informal settlementscharacterized by poor sanitary conditions, infrastructure deficiencies and lack of waste disposalservices.

In these areas, even relatively small amounts of rain can cause flooding. The naturaldrainage capability of the land has been impaired because of the extensive amounts of construc-tion, complex roadways and collection of trash and debris. Runoff is therefore six times thatwhich would occur in a natural environment, leading to hazardous conditions during rains.Flood-related accidents result in deaths of slum residents each year, many of them children.Sewers are available to only a small proportion of the population, so flooding carries faeces andspreads diarrhoeal diseases such as cholera.

Increasing variability of rainfall and more intense storms have compounded theproblems that already exist in the slums of Kampala. Climate change is likely to increase theincidence of flooding and accelerate the spread of diseases, including malaria and waterbornediseases. Climate change here has the potential to worsen poverty, especially among poorwomen, who have limited, if any, access to credit or property compared to men, and who areoften excluded from decision-making processes.

Source: Mabasi, 2009

and institutional capacity and the availability of informationto residents; but it is not necessarily the case that poorercountries or cities will always be less prepared. For example,despite being a relatively poor country, Cuba has imple-mented effective disaster preparation mechanisms. On theother hand, although the US is a relatively rich country, ithas sometimes proven to be ill prepared for disasters; forinstance, emergency response was inadequate both beforeand after Hurricane Katrina struck the city of New Orleans.

CONCLUDING REMARKSAND LESSONS FOR POLICY Climate change impacts have real implications in the urbanenvironment, many of which will continue to exacerbateexisting vulnerabilities and social issues in the future. Whilelocal climate change risks, vulnerabilities and adaptive capacity vary across cities, the global review undertaken inthis chapter reveals several key common themes.

First, climate change impacts may have compoundingeffects across many sectors of city life. The specific nature ofclimate change risks is heterogeneous around the world; butthese risks have compounding effects in nearly any context.For example, extremely high temperatures have directimpacts upon human health, placing individuals at risk ofheat-related illness or mortality. At the same time, increasingtemperatures in certain locations increase demand forenergy, which can reinforce climate change by increasinggreenhouse gas emissions and exacerbating the urban heat-island effect. Cities have inherent properties that can inter-act with climate change effects – including rapid populationgrowth, high population density, urban heat-island impactsand the presence of poverty – such that impacts that mayappear minor when considered individually may have seriouseffects when considered together in local context.

Second, climate change does not affect everyonewithin a city in the same way: gender, age, race and wealthhave implications for the vulnerability of individuals andgroups. Racial and ethnic minorities, indigenous peoples,poor populations and socially isolated individuals are highly

vulnerable to climate change impacts. The poor are oftenleast able to cope and adapt to climate change impactsbecause they have relatively few resources and tend to belocated in the most hazardous areas. Indigenous peoples,minorities and women may be explicitly or tacitly removedfrom decision-making processes and, in some cases, havelimited access to insurance, information and resources. As aresult, these groups are both less prepared for physicalhazards and less able to adapt. These effects tend to beparticularly pronounced in cities in developing countriescompared to developed countries, but are evident world-wide.

Third, planning within cities – including siting ofresidential areas, businesses and transportation infrastruc-ture – often proceeds based on historic climate data,increasing the risk of various sectors to changing conditions.Because of low land prices and less resistance fromresidents, infrastructure (including ports, water sanitationfacilities, power plants, roads and airports) tends to beconstructed in vulnerable areas. These assets are long livedand will therefore be subjected to changing conditions suchas sea-level rise, more variable precipitation and increasedintensity of storms. Failure to adjust zoning and buildingcodes and standards with an eye to the future may limit theprospect of infrastructure adaptation and place lives andassets at risk. Likewise, failure to consider the impacts ofrising populations in city planning leads to conditions thatexacerbate the vulnerability of residents to climate change,as illustrated by the case studies reviewed in this chapter.These conditions include water and other natural resourcescarcity, environmental degradation and development ofurban slums.

Fourth, climate change impacts can be long lastingand propagate worldwide. When disasters related to climatechange occur, focus on the affected areas tends to be limitedto a short period of time following the event. Yet, experiencereveals that the social and economic impacts of these disas-ters can extend for months or years. Damage to trans-portation infrastructure can interfere with a city’s ability torecover from extreme climate events. Lack of insurancecoverage can make it very difficult for individuals to cope inthe aftermath of disasters, particularly among the poor, whomay not have savings or assets to use to repair damage totheir homes or to purchase the necessities of recovery.Moreover, cities around the world, in particular large cities,are interconnected by capital and labour markets. Extremeclimate events that result in economic losses in urban areasor interruption of trade routes can thus result in long-lastingrebounding global impacts.

Fifth, limitations on governance and planning increasethe vulnerability of cities, especially in developing countries,to climate change. Poor planning resulting from scarceresources, limited information and/or political corruptionlimit the ability of cities to prepare for climate change as wellas to recover when climate-related impacts occur. In devel-oping countries, in particular, poor planning has encouragedthe development of slums and informal settlements that areprone to damage from climate-related impacts. Slum expan-sion can be difficult to control because these settlements

Urban vulnerabilityto climate changewill thereforedepend upon disaster prepared-ness


Figure 4.2

World population andrecorded natural andtechnological disasters(e.g. industrial andtransport accidents)(1950–2005)

Source: UN-Habitat, 2007, p170

World urban population

1950

Num

ber

of e

vent

s/w

orld

urb

an p

opul

atio

n (1

0 m

illio

ns) 500

400

300

200

100

0

Natural disasters

Technological disasters

1956 1962 1968 1974 1980 1986 1992 1998 2004

sometimes develop outside of the jurisdiction of localgovernment. In both developed and developing countries,inadequate preparation for climate-related disasters has ledto great losses of life and assets when individuals were notevacuated before a disaster or rapidly attended to after-wards.

Taken together, the themes discussed above suggestthat the direct and indirect impacts of climate change willcontinue to threaten the very social and economic fabric ofcities. International, national and local governments andinstitutions can benefit from the growing body of researchon climate change impacts by adjusting their policyapproaches with a mind to the future.

The many examples of climate change impactsreviewed in this chapter highlight the context-specificnature of impacts. Accordingly, policies ought to be designedto address local physical impacts and vulnerabilities to thegreatest extent possible. This does not, however, precludethe importance of national government and internationalcollaboration on the global challenge of climate change. Infact, security issues, migration and resource scarcity willoften raise issues that cross local and national boundaries.

Likewise, policies and interventions should be devel-

oped with attention to the social and economic charac-teristics of resident populations in order to reduce, ratherthan reinforce, inequalities. Care should be taken to identifywho bears the greatest burden of climate change in a givenarea and to develop policies with the goal of minimizing thisburden. Increasing the participation of groups who havebeen typically marginalized – whether indigenous groups,low-income groups, women and/or racial minorities – canhelp to both reduce the distributional impacts of climatechange and broaden the knowledge base used to tackleclimate change.

Perhaps the most important lesson for policy-makersis that climate change should no longer be considered asolely environmental challenge, addressed in isolation fromother social and economic issues. Climate change in urbanareas interferes with a wide range of existing and emergingpolicy challenges, among them poverty eradication, watersanitation, scarcity of food and water, and populationgrowth. When climate change is embraced as an integral partof these challenges, solutions can be designed to moreadequately reflect and address its myriad impacts uponcities.

1 IPCC, 2007c, Annex I, p82.2 Schneider et al, 2007, p781.3 As illustrated in Chapter 1.4 IPCC, 2001a.5 IPCC, 2007b, p30. 6 Church et al, 2004.7 IPCC, 2007b, p45.8 Thomas et al, 2004.9 IPCC, 2007b, p30.10 Thomas et al, 2004.11 IPCC, 2007b, p28.12 Scambos et al, 2004; Overpeck

et al, 2006.13 IPCC, 2007b, p45.14 Nicholls et al, 1999.15 Bigio, 2009.16 Adams, 2007.17 Ruth and Gasper, 2008.18 Definition from the National

Weather Service Glossary ofNational Hurricane Center Terms,National Weather Service(undated).

19 Areas of the Earth betweenthe tropics and polar regions:http://en.wikipedia.org/wiki/Mid-latitudes.

20 In this section of the chapter,the terms ‘tropical cyclone,’‘tropical storm’ and ‘hurricane’are used interchangeably. Definitions from the NationalWeather Service Glossary ofNational Hurricane CenterTerms, National WeatherService (undated).

21 Emanuel, 2005; Elsner et al,2008.

22 IPCC, 2007b.23 Webster et al, 2005.24 IPCC, 2007c.25 Donnelly and Woodruff, 2007.26 Vecchi and Soden, 2007.27 IPCC, 2007b.

28 Easterling et al, 2004.29 IPCC, 2007b, p30.30 Easterling et al, 2004.31 Frich et al, 2002.32 IPCC, 2007b, p30.33 Sterr, 2008.34 VanKoningsveld et al, 2008.35 Nicholls et al, 2008.36 Nicholls et al, 2008.37 Ruth and Rong, 2006.38 IPCC, 2007b, p877.39 Smyth and Royle, 2000.40 Smyth and Royle, 2000.41 Cross, 2001.42 Smyth and Royle, 2000.43 Smyth and Royle, 2000.44 UN-Habitat, 2010.45 UN-Habitat, 2003, 2009a.46 Rashid, 2000.47 Ibarrarán, 2011.48 Smyth and Royle, 2000; Cross,

2001.49 Robinson, 2001.50 Kalkstein and Davies, 1989;

Ruth et al, 2006.51 Smyth and Royle, 2000.52 IPCC, 2007b, p33.53 Meehl and Tebaldi, 2004.54 Stern, 2006, p63; IPCC, 2007b,

p53.55 A country is water stressed if

water supply acts as aconstraint on development orif withdrawals exceed 20 percent of the renewable watersupply (Wilbanks et al, 2007).

56 Bates et al, 2008, p43.57 Oke, 1982.58 Akbari, 2005.59 Akbari, 2005.60 Meehl and Tebaldi, 2004;

Schwartz and Seppelt, 2009.61 IPCC, 2007b, p53.62 IPCC, 2007b, p53; see section

on ‘Poverty’ later in thischapter.

63 IPCC, 2007b; Bates et al, 2008,p38.

64 Smyth and Royle, 2000.65 Bates et al, 2008, p85.66 Bates et al, 2008, p38.67 Folland et al, cited in Wilbanks

et al, 2007. 68 The Sunday Times, 2009.69 Symptoms of extreme drought

are widespread water short-ages or restrictions. NationalDrought Mitigation Center,2010.

70 Bates et al, 2008, p3.71 Bates et al, 2008, p26.72 Burke et al, 2006.73 Bates et al, 2008, p3.74 Bates et al, 2008, p38.75 Bates et al, 2008, pp3, 43.76 McGranahan et al, 2007.77 Choi and Fisher, 2003; Hall et

al, 2005; Kirshen et al, 2006.78 Kirshen et al, 2006.79 Definitions from United States

Geological Survey (undated):http://ga.water.usgs.gov/edu/100yearflood.html.

80 IPCC, 2007c, p48.81 This is a mid-range estimate of

sea-level rise at the end of the21st century from IPCC,2007c, p45.

82 Ruth and Rong, 2006.83 Boruff et al, 2005 (see section

on ‘Social impacts’ later in thischapter).

84 Awuor et al, 2008.85 Klein et al, 2003.86 Graves and Phillipson, 2000.87 Klein et al, 2003.88 Klein et al, 2003.89 Klein et al, 2003.

90 Sanders and Phillipson, 2003.91 Camilleri et al, 2001.92 UN-Habitat, undated.93 Transportation Research

Board, 2008, p62.94 Andrey and Mills, 2003, cited in

Wilbanks et al, 2007.95 Shukla et al, 2005.96 Transportation Research

Board, 2008, p64.97 Shukla and Sharma, undated.98 Darch, 2006.99 Kirshen et al, 2006.100 Hunt and Watkiss, 2007.101 Sailor, 2001.102 Scott et al, 1994.103 Harrison and Whittington,

2002.104 Lehner et al, 2005.105 EEA, 2005.106 IPCC, 2007f, p562.107 de Bono et al, 2004.108 IPCC, 2007f, p362.109 Ruth and Gasper, 2008.110 IPCC, 2007f, p445.111 Wilbanks et al, 2007.112 Vergara, 2005; Magrin et al,

2007; Füssel, 2009. 113 Ruth and Gasper, 2008.114 Rhodes, 1999.115 Boland, 1997.116 Bates et al, 2008, p79.117 Hunt and Watkiss, 2007, p27.118 Wilbanks et al, 2007.119 Bates et al, 2008, p92.120 IPCC, 2001a, p57; de Sherbinin

et al, 2007.121 Tanner et al, 2009.122 Environment Canada, 2001;

Kumagai et al, 2003; Hall et al,2005.

123 Rosenzweig and Solecki, 2001;Wilbanks et al, 2007, p370.

124 Wilbanks et al, 2007, p372.


The direct andindirect impacts ofclimate change willcontinue to threatenthe very social andeconomic fabric ofcities

NOTES

125 Rosenzweig and Solecki, 2001.126 World Bank, 2000; Wilbanks et

al, 2007, p371.127 UN-Habitat, 2009a, p230.128 UN-Habitat, 2009a, p230. UN-

Habitat defines ‘improveddrinking water coverage’ bythe percentage of peoplehaving access to improveddrinking water technologiessuch as piped water andprotected wells. ‘Improvedsanitation facilities’ are morelikely to separate humanexcreta from human contact(UN-Habitat, 2009a, p224).

129 Fricas and Martz, 2007.130 Kirshen et al, 2006.131 Petterson et al, 2006; Wilbanks

et al, 2007, p376.132 Wilbanks et al, 2007, p366.133 O’Brien et al, 2004; Adger et al,

2005; Kirshen et al, 2006;Wilbanks et al, 2007, p362.

134 Stern, 2006, p17.135 Kirshen et al, 2006.136 Wilbanks et al, 2007, p368.137 Kirshen et al, 2006.138 Wheaton et al, 2005.139 Bates et al, 2008, p75.140 Ruth et al, 2004; Wilbanks et

al, 2007, p368.141 Ruth et al, 2004.142 UCS, 2008.143 Defined as towards or in the

direction of a pole of the Earth(Merriam-Webster, undated).

144 Agnew and Viner, 2001; GomezMartin, 2005; Perelet et al,2007.

145 Elsasser and Bürki, 2002; Scottet al, 2007.

146 Scott et al, 2007.147 Wilbanks et al, 2007, p368.148 Hunt and Watkiss, 2007, p28.149 Lewsey et al, 2004; Wilbanks et

al, 2007, p368.150 de Sherbinin et al, 2007.151 Kont et al, 2003.152 Adger et al, 2005.153 Donner et al, 2005.154 Lewsey et al, 2004.155 O’Brien et al, 2004; Petterson

et al, 2006; Stern, 2006, p10.156 Stern, 2006, p78.157 Dlugolecki, 2001; ABI, 2005;

IPCC, 2007f, p557, p723.158 Mills, 2005.159 Kunreuther et al, 2001; IPCC,

2007f, p734.160 Petterson et al, 2006; Wilbanks

et al, 2007, p369.

161 Enz, 2000; Lewsey et al, 2004;Wilbanks et al, 2007, p369.

162 Defined here as countries withmedian per capita incomesabove US$9361 (Freeman andWarner, 2001).

163 Freeman and Warner, 2001.164 Wilbanks et al, 2007, p369.165 Petterson et al, 2006.166 Wilbanks et al, 2007, p369.167 Wilbanks et al, 2007, p371.168 Petterson et al, 2006.169 Lewsey et al, 2004.170 Grimm et al, 2008.171 The Millennium Ecosystem

Assessment was a global effortinitiated in 2001 ‘to assess theconsequences of ecosystemchange for human well-beingand the scientific basis foraction needed to enhance theconservation and sustainableuse of those systems and theircontribution to human well-being’ (ICSU et al, 2008).

172 Millennium EcosystemAssessment, 2005.

173 Syvitski et al, 2009.174 Environmental Management

Department, 2003.175 IPCC, 2007f, p362.176 Douglas et al, 2008.177 Sgobbi and Carraro, 2008.178 Uyarra et al, 2005.179 Mendelsohn et al, 2000.180 McLeman and Smit, 2005.181 Beniston and Diaz, 2004.182 Beniston and Diaz, 2004.183 Basu and Samet, 2002.184 Beniston and Diaz, 2004.185 Haines et al, 2006.186 Basu and Samet, 2002.187 Rosenzweig and Solecki, 2001. 188 Basu and Samet, 2002.189 Lee, 1980.190 Wolfe et al, 2001; Basu and

Samet, 2002.191 Costello et al, 2009.192 BBC News, 2010a.193 As of 1 August 2010; BBC

News, 2010b.194 Meusel and Kirch, 2005.195 Ahern et al, 2005.196 Silove and Steel, 2006.197 Akbari, 2005.198 Patz et al, 2005.199 Tanser et al, 2003.200 McMichael et al, 2003. 201 Bartlett, 2008.202 UN-Habitat, 2006.203 Hardoy and Pandiella, 2009.204 Hardoy et al, 1992, 2001.

205 McGranahan et al, 2007. 206 See Awuor et al (2008) for

Mombasa (Kenya); Revi (2008)for cities in India; Alam andRabbani (2007) for Dhaka(Bangladesh); and Dossou andGlehouenou-Dossou (2007)for Cotonou (Benin); alsoAdelekan (2010) for Lagos.

207 See Nchito (2007) for Lusaka(Zambia); and de Sherbinin etal (2007) for Rio de Janeiro(Brazil).

208 Hardoy and Pandiella, 2009.209 Satterthwaite et al, 2007a; UN,

2009. However, note that it isthe disasters in the developedcountries that generally havethe highest economic costs (atleast in absolute terms).

210 Bull-Kamanga et al, 2003; UN-Habitat, 2007; UN, 2009.

211 Bartlett, 2008.212 Revi, 2008, p219.213 UN, 2007, p80.214 Adger, 1999, 2000.215 UNDP, 2007, p74.216 See, for example, African

Development Bank et al(2003).

217 Alber, 2010.218 Neumayer and Plümper, 2007.219 UNDP, 2007, p77.220 Oxfam, 2005.221 Toulemon and Barbieri, 2008.222 Bartlett, 2008.223 Neumayer and Plümper, 2007.224 Enarson, 2000.225 Enarson, 2000.226 Enarson and Phillips, 2008.227 Enarson, 2000.228 WEDO, 2008, p55.229 Overstreet and Burch, 2009.230 Enarson, 2000.231 Brookings Institution, 2009.232 Ruth and Ibarrarán, 2009.233 Schroeder, 1987.234 WEDO, 2008, p55.235 Bartlett, 2008.236 Ruth and Ibarrarán, 2009, p61.237 Bartlett, 2008.238 McMichael et al, 2003.239 Langer, 2004.240 Ruth and Ibarrarán, 2009, p61.241 Fothergill et al, 1999.242 UN-Habitat, 2006.243 Ruth and Ibarrarán, 2009.244 Fothergill et al, 1999.245 Brookings Institution, 2009.246 Langer, 2004.247 UN-Habitat and OHCHR,

2010.

248 Macchi, 2008, p19.249 UNDP, 2009, p9.250 UNDP, 2009, p15.251 OCHA and IDMC, 2009.252 Reuveny, 2007.253 Alston et al, 2001.254 Rain et al, 2011.255 Raleigh et al, 2008.256 UNDP, 2009, p45.257 See Myers, 1997. See also Stern

Review Team, 2006. Thisestimate is tentative, and Myershimself has acknowledged thatthe figure is based upon ‘heroicextrapolation’ (see Brown,2007, p6).

258 Myers, 2005.259 Tacoli, 2009.260 Reuveny, 2007.261 UNDP, 2007, p24.262 Kumssa and Jones, 2010.263 At the 5663rd Meeting of the

Council in 2007, representa-tives from across the worldechoed the belief that climatechange issues could have realnational and internationalimplications, and that theseissues ought to be addressed ina global forum (UN, 2007).

264 Gulden, 2009, p187.265 UN-Habitat, 2007.266 Cross, 2001.267 Klein et al, 2003.268 Cross, 2001.269 Klein et al, 2003.270 UNDP, 2007.271 Nicholls and Tol, 2007.272 Ruth and Ibarrarán, 2009.273 WHO, 2010.274 Benson and Clay, 2004.275 UNDP, 2007, p93.276 Romero Lankao, 2009.277 Romero Lankao, 2009.278 Ruth and Gasper, 2008.279 UN, 2007, p80.280 UN-Habitat, 2010, p32.281 UN-Habitat, 2003, p13.282 Douglas et al, 2008.283 Cambell-Lendrum and

Corvalan, 2007.284 UN-Habitat, 2007, p170.285 Tanner et al, 2009.286 Smyth and Royal, 2000.287 See UN Habitat, 2007, on the

trends of natural and human-made disasters in cities.

288 ISDR Terminology:www.unisdr.org/eng/library/lib-terminology-eng home.htm,last accessed 1 November2010.


Mitigation – the reduction of greenhouse gas (GHG)emissions and their capture and storage – has been at theheart of policy responses to climate change over the past twodecades. At the international level, the 1992 United NationsFramework Convention on Climate Change (UNFCCC) hasas its core objective the ‘stabilization of greenhouse gasconcentrations in the atmosphere at a level that wouldprevent dangerous anthropogenic interference with theclimate system’.1 Subsequent agreements, including the1997 Kyoto Protocol and the 2009 Copenhagen Accord,have developed targets and timetables for the internationalcommunity to reduce GHG emissions.2 Many nationalgovernments have made commitments which go beyond therather modest goals that have so far been agreed internation-ally. However, achieving these international and nationalambitions is dependent on the implementation of policiesand measures to reduce or capture GHG emissions on theground. Cities are therefore critical places for achievingmitigation. As Chapter 3 has shown, a significant proportionof GHG emissions arise from activities undertaken in urbanareas.3 Cities represent concentrations of population andeconomic activities, with growing demands for energy fordomestic services such as heating, cooling and lighting, aswell as commercial buildings, industrial processes, telecom-munications systems, the provision of water, the productionof waste, leisure activities, travel and so on. Cities can there-fore be seen as part of the problem of climate change and

reducing GHG emissions in cities is a key policy challenge(see Table 5.1).

However, cities can also be seen as part of thesolution to addressing climate change (see Table 5.1), both interms of the role of urban governments and because of thepotential for private-sector and civil society actors to respondto climate change at the urban level. Municipal authoritiesare potentially important actors in tackling the challenge ofmitigation for three reasons. First, they have jurisdictionalresponsibility for key processes – land-use planning, trans-portation, waste collection and disposal, and energy cons-umption and generation – which shape GHG emissions.Second, the concentration of people/business in urban areasmeans that solutions (e.g. mass transit or requirements forenergy savings in offices) are feasible. In other words, citiescan act as laboratories where solutions for addressingclimate change can be tried and tested. Third, municipalgovernments also provide a key interface for engagementwith stakeholders in the private sector and civil society. It isincreasingly clear that non-governmental actors have a signif-icant role in addressing climate change at the urban level.Private-sector organizations and civil society groups are nowinvolved in a range of measures (e.g. promoting behaviouralchange and reducing energy use in commercial buildings)independently of local and national governments.

Over the past two decades, cities have provided acrucial arena within which the challenges of climate change

Mitigation – thereduction of greenhouse gas(GHG) emissionsand their captureand storage – hasbeen at the heart ofpolicy responses toclimate change overthe past two decades

Municipal authorities are …important actors intackling thechallenge of mitigation

C H A P T E R

CLIMATE CHANGE MITIGATIONRESPONSES IN URBAN AREAS

5

Part of the problem Part of the solution

• In 2010, half of the world’s population lived in cities.a • Municipal authorities have responsibility for many processes that affect • Between 2010 and 2020, 95% of the global population growth GHG emissions at the local level.

(766 million) will be urban residents (690 million), and the bulk of • Municipalities can act as a ‘laboratory’ for testing innovative approaches.these (632 million) will be added to the urban population of • Municipal authorities can act in partnership with private-sector and developing countries.a civil society actors.

• Between 2000 and 2010, the number of slum dwellers in developing • Cities represent high concentrations of private-sector actors with countries increased from 767 million to 828 million. The figure might growing commitment to act on climate change.reach 889 million by 2020.b • Cities provide arenas within which civil society is mobilizing to address

• Cities represent concentrations of economic and social activities that climate change.produce GHG emissions.c

• Cities and towns produce between 40 and 70 per cent of global anthropogenic GHG emissions.c

• By 2030, over 80 per cent of the increase in global annual energy demand above 2006 levels will come from cities in developing countries.d

Sources: a UN, 2010; b UN-Habitat, 2010; c see Chapter 3; d IEA, 2008, 2009

Table 5.1

Cities and the mitigation of climatechange

mitigation are being addressed. During the 1990s, theseresponses were primarily concentrated in developedcountries and undertaken through three internationalmunicipal networks: Local Governments for Sustainability’s(ICLEI’s) Cities for Climate Protection Campaign (CCP), theClimate Alliance and Energie-Cités.4 During the 2000s, thecities involved in responding to climate change have grownin number and now include cities in the developing world, inpart facilitated by the emergence of new international initia-tives such as the Cities Climate Leadership Group (C40), aswell as the continuing work of more established networks.5

Despite this recent growth in interest, and in their potentialsignificance in responding to climate change, the under-standing of how and why cities are responding to climatechange remains limited, particularly in developing countries.Studies of the responses to the issue of climate changemitigation in cities rely heavily on individual case studiesfrom ‘pioneering’ cities in developed countries,6 with somenotable exceptions.7 This body of research suggests that theresponse of cities to the challenges of mitigation has beenfragmented,8 that significant gaps exist between the rhetoricof addressing climate change and the realities of action onthe ground,9 and that the possibilities, and responsibilities,for acting to reduce GHG emissions vary significantlybetween cities.10 In short, attempts to mitigate climatechange in cities have been far from straightforward.

Given that cities lie at the heart of the contemporaryneo-liberal political-economic model, this is not surprising.Cities are pivotal sites in the ‘metabolism’ of naturalresources and the consequent production of GHG emissions,upon which this model of development rests:11

... cities have extended their ecological hinter-land by importing natural resources orresource-based infrastructure services, likeelectricity … from afar, but also by using ecosys-tems far beyond the urban bioregion as sinks fortheir emissions. The patterns of modern urban-ization have thus been highly dependent on thefunctioning of the networks driving materialflows in and throughout the city.12

This pattern of urbanization and its environmental conse-quences has been uneven. While cities in the developedworld have historically been the source of the bulk of urbanGHG emissions, as the location of production of goods andservices shifts to cities in developing countries so do environ-mental burdens. At the same time, as the consumption ofenergy-intensive goods and services increases amongst afflu-ent sectors of urban societies in developing countries, so toowill GHG emissions. However, the levels of GHG emissionsfrom poor urban populations remain negligible, suggestingthat urban efforts to mitigate climate change need to betargeted at cities where there is both a responsibility and acapacity to act. Furthermore, climate change will deepen arange of existing inequalities; thus, discussions of climatechange mitigation in cities need to include broader concernsabout the vulnerability of different social groups. Specif-ically, the gender dimension of climate change mitigation,

and the potential for women to contribute to climate changemitigation strategies, has not yet been fully acknowledged.13

The result is a complex geography of urban GHGemissions,14 where responsibility for action, and the capacityto act, rest with affluent urban societies, but where thebrunt of the future impacts of climate change will be borneby vulnerable urban populations.15 In this context, buildingan understanding of how cities in developed countries areresponding to the challenge of climate change mitigation –beyond the small number of case studies currently available– is a critical task. At the same time, there is a need to under-stand how climate change mitigation is being addressed inthe world’s megacities, which because of their sheer size arepotentially critical sites of current and future GHG produc-tion, as well as the small urban centres within which thebulk of population growth and energy demand over the nextfew decades is forecast to occur.16 In Asia and Latin America,recent industrialization and the growth of affluent urbancommunities suggests that climate change mitigation may bean increasingly pressing challenge.

This chapter seeks to address these knowledge gapsby providing a review of urban responses to climate changein a comparative context. It focuses on the responses of so-called ‘global’ cities (those regarded as having partic-ular strategic economic and/or political importance)17 andmegacities (those with a population of more than 10 millionpeople). These cities are critical to the urban mitigation ofclimate change both because of their current and potentialcontribution to GHG emissions and their wider economicand political influence.18 First, the chapter considers thepolicy responses and initiatives that are emerging in cities.Second, it examines how such strategies and measures havebeen undertaken through different modes and mechanismsfor governing climate change in the city. Third, the chapterassesses the opportunities and constraints that cities haveencountered in institutional, economic, technical and politi-cal terms, before, fourth, providing a comparative analysis ofemerging trends in urban responses to climate change.Finally, the chapter offers some concluding comments andlessons for policy.

RESPONSES TO CLIMATECHANGE MITIGATION IN URBAN AREASOver the past two decades, municipal authorities haveengaged in the development of urban climate changepolicies as well as initiatives and schemes to reduce GHGemissions in the city. More recently, a range of other actors –including non-governmental organizations (NGOs), donoragencies and private corporations – have also becomeinvolved in urban climate change mitigation initiatives. Thissection reviews different policy approaches that municipali-ties have developed for dealing with climate changemitigation before considering the strategies and measuresthat have been adopted by both public and private actors infive key sectors: urban development and design; built

Over the past twodecades, cities haveprovided a crucialarena within whichthe challenges ofclimate changemitigation are beingaddressed

Responsibility foraction, and thecapacity to act, restwith affluent urbansocieties, but … thebrunt of the futureimpacts of climatechange will beborne by vulnerableurban populations


environment; urban infrastructures; transport; and carbonsequestration.

Municipal policy approaches

The policy approaches adopted by municipal governments toaddress the mitigation of climate change in urban areas varyconsiderably in terms of the sources of GHG emissions thatare targeted – whether these are from the municipalities’own activities or from across the urban community – andwhether they are undertaken on a strategic or ad hoc basis(see Table 5.2). In each case, a variety of mechanisms fordeveloping and implementing climate change mitigationmeasures have been used.19

Municipalities have undertaken ad hoc measures toreduce GHG emissions from their own operations, often ona reactive basis – for example, in response to a particularfunding opportunity or the initiative of an individual (seeTable 5.2). Municipal authorities have also been opportunein developing one-off schemes or projects at the communityscale, often in collaboration with other partners. Such ad hocapproaches are popular and ‘numerous cities, which haveadopted GHG reduction targets … prefer to implement …measures on a case by case basis’.20 The wide range andsignificant number of such ad hoc responses suggest thatgiven the right financial and political conditions, municipalgovernments have been more than able to respond positivelyto the challenges of mitigating climate change.

Strategic approaches, in contrast, have usually beendeveloped where there has been access to secure funding,new institutional structures – such as a central unit foraddressing climate change – and strong political support foraction. These can either involve setting out a programme ofgoals and measures through which municipalities seek toreduce their own GHG emissions over the medium to longterm (a managerial approach), or a comprehensive approach,developed by only a few municipalities, involving targetsetting, planning and the development of initiatives at thecommunity level.21 Such strategic approaches were firstpromoted by ICLEI’s CCP Milestone programme establishedduring the mid 1990s (see Box 5.1). A similar approach hasalso been adopted by the Climate Alliance in its ClimateCompass initiative (see Box 5.2). Evidence suggests thatsome substantial reductions in GHG emissions have beenachieved by these means. For example, in 2006, 546 localgovernments in 27 countries were members of the CCPcampaign, accounting for 20 per cent of global GHGemissions. Estimates suggest that the annual emission reduc-tion by these cities was 60 million tonnes of CO2eq, whichamounts to a 3 per cent annual reduction among the partici-pants and 0.6 per cent globally.22 However, while thosemunicipalities that have focused on their own operationshave made substantial progress against their targets, achie-ving such goals beyond the confines of the municipality itselfhas been both more difficult to monitor and more challeng-ing to implement.

Despite differences in the approaches that municipali-ties have adopted to the formation and implementation ofclimate policy, research suggests that attention has primarily

been focused on initiatives in the energy sector, and inparticular on improving energy efficiency.23 Energyefficiency is a particularly potent issue as it can ‘advancediverse (and often divergent) goals in tandem’,24 serving totranslate various interests into those concerning climate

93Climate Change Mitigation Responses in Urban Areas

Table 5.2

Typology of policyresponse to climatemitigation in the urbanarena

Box 5.1 Strategic approaches to urban climate change policy: The CCP Milestone Methodology

• Milestone 1: establish an inventory and forecast for key sources of GHG emissions in thecorporate (municipal) and community areas, and conduct a resilience assessment to deter-mine the vulnerable areas based on expected changes in the climate.

• Milestone 2: set targets for emissions reduction and identify relevant adaptation strategies.• Milestone 3: develop and adopt a short- to long-term local action plan to reduce emissions

and improve community resilience, addressing strategies and actions for both mitigationand adaptation.

• Milestone 4: implement the local action plan and all the measures presented therein.• Milestone 5: monitor and report on GHG emissions and the implementation of actions and

measures.

Source: www.iclei.org/index.php?id=810, last accessed 18 October 2010; see also Box 2.7

Box 5.2 Strategic approaches to urban climate change policy: The Climate Alliance’s Climate Compass

Module 1 – Initiation:• informing relevant departments of the administration;• clarifying needs and expectations;• raising awareness of local climate change policies;

Module 2 – Inventory:• analysing the setting;• surveying previous priorities and activities;• characterizing the initial conditions;

Module 3 – Institutionalization:• building organizational structures;• assigning responsibilities and nominating persons in charge;• forming a Climate Compass working group;

Module 4 – Climate action programme:• defining targets;• selecting priority measures;• formulating strategic resolutions (on criteria, standards, etc.);• agreeing the mid- and long-term climate strategy;

Module 5 – Monitoring and reporting:• developing indicators;• collecting data for CO2 monitoring;• preparatory work for future reporting.

Source: www.climate-compass.net/_modules.html, last accessed 18 October 2010

Ad hoc Strategic

Municipality Reactive ManagerialCommunity Opportune Comprehensive

change and effectively forging new partnerships. Whileenergy efficiency still dominates many municipal responsesto mitigating climate change, the growing diversity of thosecities involved in mitigating climate change together withthe range of private-sector and civil society actors becominginvolved with this policy agenda has led to a growing array ofprojects and measures being adopted.

Nonetheless, it is possible to identify five key sectorsin which urban responses to mitigating climate change havebeen concentrated: urban form and structure; built environ-ment; urban infrastructures; transport; and carbon seques-tration. Reviewing the evidence across these sectors, thefollowing sections examine the range of activities beingundertaken by municipal authorities and other actors in thecity to reduce GHG emissions and the strengths andweaknesses of the initiatives that have been undertaken.

Urban development and design

The use of energy within a city, and the associated produc-tion of GHG emissions, is dependent on both the form ofurban development (i.e. its location and density) and itsdesign.25 As urbanization continues apace, one of the criticalchallenges is managing the process of urban developmentand, in particular, the twin challenges of urban sprawl andthe growth of informal urban settlements (see Box 5.3).26

Urban sprawl is an increasing challenge for cities in devel-oped and developing countries. As the distances betweenhome, work, education and leisure activities increase, sooften does the reliance on private motorized transport. Insome cities sprawl has meant the development of middle-class urban fringe districts where dwelling sizes tend toincrease, leading to an increase in per capita GHG emissions.In other cities, sprawl is fuelled by the growth of informalsettlements. Between 2000 and 2010 the number of slumdwellers in developing countries increased from 768millions to 828 million, and estimates suggest that thenumber of slum dwellers will increase to 889 million by2020.27 Slum populations lack adequate access to reliable

and affordable energy supplies and shelter, meaning that, inparallel with the other significant challenges that such settle-ments pose for sustainability and well-being, manyhouseholds are unable to heat or cool their dwellings effec-tively and experience fuel poverty.

In seeking to address these challenges, various strategies of land-use planning, including land-use zoning,master-planning, urban densification, mixed-use developmentand urban design standards, have been used in order to limiturban expansion, reduce the need to travel and increase theenergy efficiency of the urban built form.28 Such approachescan be deployed at a range of locations within the city and atdifferent scales (see Table 5.3). Overall, research suggeststhat large-scale schemes, including large regenerationprojects, projects to prevent urban expansion and the reuseof derelict land appear to be a more common response formitigating climate change than small regeneration projects.Most such projects are undertaken in developed countries. Indeveloping countries, there are few initiatives to explicitlymitigate climate change through urban design and develop-ment, and where they do exist, the local governments’capacity to implement such measures is often limited.

Most often, these projects are led by municipalauthorities through the use of planning regulations andplanning guidance. This is the case, for example, of theprinciples of ‘compact city planning’29 incorporated withinthe municipal ordinances of cities such as São Paulo (Brazil)and Cape Town (South Africa),30 although, in practice, it isnot clear that such principles can actually be implemented inan effective way. These principles advocate a combination ofplanning measures to combine high-density developmentand mixed land-use principles to prevent urban sprawl andreduce the dependence on motorized transport, while focus-ing on the integration of green areas in the city. Althoughthis principle may appear to be linked with more sustainableurban form models, research in developed country cities31

suggests that the effectiveness of the compact city model inreducing GHG emissions depends on the lifestyle and spacedemands of the city inhabitants.

Alongside initiatives undertaken by municipal authori-ties, particularly in developed countries, private developersand community groups have led new urban development,brownfield regeneration and neighbourhood renewalprojects which seek to address climate change specifically,such as the Onion Flats in Philadelphia (US), the GreenBuilding in Manchester (UK), the A101 neighbourhood inMoscow (Russia) and the project T-Zed in Bangalore(India).32 The combination of sustainability and climatemitigation objectives with business interests has led to thedevelopment of large-scale flagship urban developments thatmay bring together local and international partners toadvance economic interests alongside environmental ones.One famous example from China was the proposed eco-cityDongtan, in Shanghai’s ‘last piece of pristine land’ in Chong-ming Island. The developer, Shanghai Industrial InvestmentCorporation, contracted Arup, the international professionalservices firm in 2005 to design a master plan for Dongtan asan ‘experiment’ to showcase a national model for sustainabil-ity, energy efficiency and environmental awareness.33 Some

Various strategies ofland-use planning …have been used inorder to limit urbanexpansion, reducethe need to traveland increase theenergy efficiency ofthe urban built form

In developingcountries, there arefew initiatives toexplicitly mitigateclimate changethrough urbandesign and development

In developedcountries, privatedevelopers andcommunity groupshave led new urbandevelopment,brownfield regeneration andneighbourhoodrenewal projectswhich seek toaddress climatechange


Box 5.3 Urban development challenges for mitigating climate change: Thailand and Canada

In Chiang Mai (Thailand), research found that urban and commercial development coupled withgrowing economic prosperity has led to a surge in personal vehicle usage, related to both workcommuting and leisure. The number of registered passenger cars and motorcycles increasedmore than 20-fold between 1970 and 2000, while the population only doubled, with a significantimpact on greenhouse gas (GHG) emissions.a

Few Canadian cities appear to be prioritizing climate change-related action in land-useplanning. While most cities do not acknowledge the emission reduction benefits of growthmanagement and increased density, Calgary, Vancouver and Toronto are making explicit connec-tions between land use and emissions. Yet, even in these three cities – which are leading climatechange action in Canada – few specific initiatives address these connections. Research hasattributed this to two main reasons: first, cities depend on provinces to review land-useplanning policies, and this relationship may act in delaying or even discouraging action in thisarea; and second, actions required may be extremely divisive, openly challenging the traditionalpreference for suburban development in Canada.b

Sources: a Lebel et al, 2007, p101; b Mackie, 2005; Gore et al, 2009, p11

commentators, however, cast doubt on whether the Dongtanplans will ever be realized.34 Whether the reason is the lackof leadership,35 the conflicts of interest between local devel-opers and international partners36 or the permissive policiesof local authorities,37 many have criticized the project as notoffering real solutions to address climate change.38

Furthermore, even where individual developmentsmay be successful, the logic of developing greenfield urbanfringe sites as a means of addressing climate change mitiga-tion can be questioned, both in terms of their overall carbonfootprint and, because of their exclusive nature, their poten-tial for exacerbating social inequalities. Despite thesecriticisms, the trend for developing new ‘eco-cities’ showslittle sign of abating in developed and developing countriesalike. For example, the Clinton Climate Initiative hasrecently launched the Climate Positive programme, focusingon large-scale developments in 17 cities on six continentswhich are aiming to become carbon neutral.39 A contrastingtrend is the proliferation of initiatives, primarily in developedcountries for the regeneration of brownfield land and neigh-bourhood renewal, which combine social and environmentaljustice objectives (see Box 5.4).

While municipal authorities can be crucial to thedevelopment of these projects, grassroots civil society organ-izations are also important. In the US, the Tent City projectin Boston, the Plaza Apartments in San Francisco and theIntervale Green and Louis Nine House in New York40 are allassociated with civil society actors, sometimes led by NGOs,and have sought to promote carbon-saving technologies assuitable cheap alternatives for providing energy to low-income residents.

The confluence of a variety of interests and materialcircumstances in initiatives to mitigate climate changethrough urban design and development makes them complexand difficult to manage. The development and implementa-tion of ‘low-carbon’ planning principles by municipal govern-ments may encounter political opposition, lack enforce-ability, and have limited impacts upon the behaviour ofindividuals who live and work in the city. Furthermore, suchprinciples may be socially divisive, reinforcing patterns ofinequality in the city by creating enclaves of ‘sustainable’living while failing to address the basic needs of the majorityof urban citizens. Moreover, gender concerns have not been fully integrated within climate change policies andplanning.41

In terms of low-carbon urban development projects,the circumstances that lead to their inception may changerapidly, thus challenging their feasibility, as was the case inthe Dongtan project in Shanghai (China). One means ofensuring the long-term feasibility of such schemes is to takeother issues of social and environmental justice into consid-eration, either through public consultation or through theparticipation of a range of stakeholders in the design andmanagement of the project. Current examples suggest thatsmall-scale developments which aim to simultaneouslyaddress environmental and social issues (e.g. homelessness,poverty, etc.) are more likely to find support from civilsociety groups, who in turn can facilitate their implementa-tion. This, however, does not dismiss the idea that visionary

cutting-edge projects may be able to provide best practiceexamples to challenge current socio-technical barriers, butsuggests that the focus needs to change towards the devel-opment of projects that can address global demands forclimate change mitigation and local demands for quality oflife.

Built environment

The design and use of the built environment is a criticalarena for climate change mitigation because ‘the buildingsector consumes roughly one-third of the final energy usedin most countries, and it absorbs an even more significantshare of electricity’.42 The built environment includes public(e.g. government offices, hospitals, schools) domestic (hous-ing) and commercial/industrial (e.g. offices, factories) build-ings, with the latter increasingly recognized as important indriving peak demand and significant sources of GHG emis-sions in cities in developing countries.43 The use of energywithin the built environment is the result of complex inter-actions among building materials, design, the systems used

The design and use of the built environment is acritical arena forclimate changemitigation


Box 5.4 Sustainable living and brownfield development, Stockholm, Sweden

Hammarby Sjöstad, Stockholm’s largest new urban development project, is a model for closed-loop sustainable urban development. Their strategy is outlined in the Hammarby Model, aneco-cycle that optimizes resource use and minimizes waste in order to meet a wide range ofsustainability targets in the areas of land use, energy, water, transport, building materials andsocio-economic indicators. The new district, expected to house 25,000 inhabitants, is built on200ha of industrial and harbour brownfield land in southern Stockholm, using tested eco-friendly building materials.

The district has its own recycling model, an underground vacuum-based system, whichreduces waste and its associated collection costs (by 40 per cent overall, and 90 per cent fornon-recyclable waste). Rainwater harvesting and the diversion of storm water from the sewer-age system to be reused for heating, cooling and power generation help to offset demands forboth water and power. The Hammarby district achieves 100 per cent renewable energy in itsdistrict heating network and transport use by making use of heat recovery from waste incinera-tion, and biogas from the digestion of organic waste and sludge for household and transportuse. Rooftop solar panels are also widely employed.

Suggested reasons for the successful realization of the Hammarby project (due to becompleted in 2015) include acknowledgement of Stockholm’s strong leadership in sustainabledevelopment planning; the implementation of innovative policies, high stakeholder involvementand commitment; and the successful coordination between and within the municipality and theSwedish national government.

Source: Hammarby Sjöstad, 2010

Type of scheme Description

Urban expansion, informal Application of land-use planning and design policies to limit energy settlements or suburban use in the expanding areas of existing cities.development:New urban development: Application of land-use planning and design policies to limit energy

use in new urban areas.Reuse of brownfield land: Urban development on old industrial or other derelict areas of the

city to encourage densification, mixed-use development and reduce energy use in the city.

Neighbourhood and small-scale Schemes which seek to renew existing housing stock and redevelop urban renewal: urban layout and design at a neighbourhood or street scale in order

to reduce energy use in the city.

Table 5.3

Climate change mitigation throughurban development and design

to provide buildings with energy and water, and the ways inwhich buildings are used on a daily basis.44 Gender differ-ences may play an important role in how energy within thehousehold is used.45

Policy approaches for reducing GHG emissions fromthe built environment have primarily focused on issues ofenergy efficiency, with approaches grouped into ‘threecategories: economic incentives (e.g. taxes, energy pricing);regulatory requirements (e.g. codes or standards); or infor-mational programmes (e.g. energy awareness campaigns,energy audits)’.46 More recently, there has been a growth involuntary rating systems (e.g. Energy Star in the US and theCarbon Trust Standard in the UK) and in the involvement ofprivate actors (e.g. the C40 and Clinton Climate Initiative) inschemes to reduce energy use, which has led to an increasein expectations concerning energy efficiency in the

(commercial) built environment. This combination of finan-cial, regulatory, education-based and voluntary mecha-nisms47 has led to an explosion in the range of schemesdeployed to address energy use in the built environment,which has also been assisted by the development of micro-generation technologies and new building materials (seeTable 5.4).

Despite the potential range of initiatives that could beundertaken, measures in the built environment sector tendto focus on energy-efficient technologies, alternative energysupply technologies and demand-reduction practices.Existing evidence suggests that initiatives in the builtenvironment sector have primarily been located in cities indeveloped countries.48 In particular, efforts have beenconcentrated on retrofitting existing buildings, those whichare municipally owned and in the residential sector, withenergy-efficient technologies – for example, in the Europeancities of Vienna (Austria), Stockholm (Sweden), London(UK), Munich (Germany) and Rotterdam (The Netherlands)(see also Box 5.5). National governments in developed coun-tries have also intervened in implementing retrofitting prog-rammes at the local level. For example, the US Departmentof Energy has led the Weatherization Assistance Program,which since 1999 has sought to increase the energyefficiency of low-income households while ensuring theirsafety in New York and other US cities.49

Research also suggests that in developed countries,many successful projects are led by grassroots organizationsand housing co-operatives, such as the case in Tel Aviv(Israel), where a group of house buyers announced in 2009the launch of the first Tel Aviv ecological housing project.50

This suggests that innovative forms of social organization areemerging to coordinate and lead initiatives to addressclimate change in the built environment, with significantpotential for addressing issues of social and environmentaljustice. Private developers may also have a strong role inpromoting and implementing sustainable technologies.However, dealing with existing building stock posesproblems in terms of conservation of heritage and dealingwith demolition materials: in the UK, in order to achieve theexisting targets for GHGs emission reductions, higher ratesof demolition are advocated if sustainable technologies alonecannot meet the heating needs of insufficiently insulatedhousing.51

Despite the focus on measures to address climatechange in the built environment, few cities in developedcountries have sought to develop energy-efficient buildingmaterials or to address issues of the sustainable supply anduse of water. However, when the intention is to establishbest practice examples or to showcase new technologies,projects often include a range of different measures, includ-ing novel materials as well as low-carbon energy and watersystems and passive designs. The ability of these measures tomake significant gains in emissions reductions will dependon the current building standards, which vary greatly fromcity to city. Universities, architectural practices and engin-eering firms have been important sources of innovation,leading pilot projects designed to showcase a range oftechnologies.52 The use of energy-efficient materials is not

Policy approachesfor reducing GHGemissions from thebuilt environmenthave primarilyfocused on issues ofenergy efficiency



Energy-efficient materials: The use of energy-efficient materials in the construction of the built environment.

Energy-efficient design: The use of energy- and water-efficient design principles, such as ‘passive’ heating and cooling.

Building-integrated The use of renewable and low-carbon energy technologies to provide alternative energy supply: energy to individual buildings.Building-integrated The use of off-grid water supply and processing techniques which reduce alternative water supply: energy use in the production and heating of clean water.New-build energy and The use of energy- and water-efficient devices in the construction and water-efficient technologies: development of new buildings.Retrofitting energy- and The use of energy- and water-efficient devices in the renovation of water-efficient technologies: existing buildings.Energy- and water-efficient The use of efficient appliances within the built environment.appliances:Demand-reduction Measures aimed at reducing the demand for energy and water within measures: the built environment.

Table 5.4

Climate change mitigation in the built environment

Box 5.5 Retrofitting domestic, public and commercial buildings in the UK and the US

• London (UK): the Carbon 60 project followed the commitment of the Sandford HousingCo-operative to reduce greenhouse gas (GHG) emissions by 60 per cent. The combinedfinancial support from private energy companies, the UK government and the rentincreases within the co-operative made possible the retrofitting of 14 houses with woodpellet boilers and solar water heating.a

• Birmingham (UK): the Summerfield eco-housing project in Birmingham (supported byBirmingham City Council and Urban Living and the Family Housing Association) developeda demonstration project in a Victorian house featuring solar photovoltaic panels; greywater recycling and air source heat pumps; sunpipes; high-performance insulation madefrom recycled paper, denim and sheep’s wool; and kitchens made from recycled materials.b

• Manchester (UK): the Cooperative Insurance Services ‘Tower’ was built in 1962 and is thetallest office building in the UK outside of London. In 2004, the Cooperative FinancialServices started a UK£5.5 million project to retrofit photovoltaic technology, funded bythe Northwest Regional Development Agency.c

• Philadelphia (US): the Friends Center Building Project, initiated in 2006, involves the retro-fitting of an 1856 building with sustainable technologies. The project integrates recycledmaterials, recycled construction waste, white roof, and windows with spectrally selectiveglass, alongside sustainable and renewable technologies (e.g. geothermal exchange; solararray; wind power; storm water capture and reuse) and green building design with naturallight.d

Sources: a Sanford Housing Co-operative, undated; b Office of the Deputy Prime Minister, 2003; c Energy PlanningKnowledge Base, undated; d www.friendscentercorp.org, last accessed 18 October 2010

only possible in individual household projects, but can alsobe promoted as a strategy for commercial projects or, morewidely, to encourage social and environmental sustainability(see Box 5.6).

In cities in developing countries there has been lessemphasis on retrofitting residential buildings or on reducingdemand for energy and water use. However, initiatives havebeen established to install energy-efficient appliances inmunicipal buildings in several cities, including Mexico Cityand Cape Town (South Africa),53 and to reduce energy use incommercial buildings, especially in cities in Asia.54 Inaddition, the use of energy-efficient materials has been animportant means through which municipal governments andother actors have sought to address GHG emissions reduc-tions and the provision of low-cost housing to low-incomegroups. South American cities such as Buenos Aires(Argentina) and Rio de Janeiro (Brazil) have piloted the use ofenergy-efficient and low-cost materials to deliver sustainablehouses in low-income areas. In June 2009, the ArgentinianMinistry of Infrastructure signed a contract with theHousing Institute, the National University of La Plata and theNational Institute of Industrial Technology to start a pilotproject to deliver social housing ‘bioclimatic houses’ inBuenos Aires.55

In addition to measures to improve energy efficiencyand reduce demand, cities are also experimenting with alter-native forms of renewable and low-carbon energy supply. Inthe built environment, initiatives have primarily focused onthe use of solar water heaters, relatively simple devices usedto heat water using sunlight,56 rather than other auton-omous energy supply devices, such as photovoltaic cells,wind power or biomass technologies. Some cities – such asBarcelona (Spain), São Paulo (Brazil) and Buenos Aires(Argentina) – enforce the adoption of solar water heaters inmunicipal ordinances. In China, given its leading position inthe manufacture of domestic solar water heaters, there ispotential for this technology to be widely adopted. The mainbarrier for the adoption of solar water heaters is their largeinitial installation cost; but given that solar water heatershave a longer lifetime, the overall costs of solar water heatersmay be considerably lower.57 A study of a project to install200,000 solar water heaters in the quickly urbanizing andindustrializing district of Yinzhou (China) concluded thatsuch a project could have significant benefits (see Table 5.5).In addition to their climate change benefits, the decentral-ization of energy provision is often seen as a way ofaddressing the energy needs of those actors who do not haveaccess to a reliable supply of energy. From a gender perspec-tive, low-carbon options for cooking, such as biogas digestersand solar cookers, may facilitate women’s access to energy aslong as they are adapted to the local context and compatiblewith women’s daily routines and workloads.58

Within the built environment, the potential formitigation gains from reducing the demand for energy is alsosignificant. Municipal governments, private-sector compa-nies and civil society groups have undertaken a wide range ofinitiatives aimed at changing the ways in which their ownemployees and urban citizens use energy. To date, theseefforts have not taken issues of gender into account.59 This

could be a critical omission as women are often thought to have a greater share of decision-making within the household. For example, in Organisation for Economic Co-operation and Development (OECD) countries, women makeover 80 per cent of consumer decisions in the household60

and thus may determine the sustainable consumptiondecisions within the home. In general, women appear to bemore prepared for behavioural changes than men, as mentend to rely most on technological solutions. For example,women tend to place more emphasis on eco-labelled food,recycling and energy efficiency than men.61 This suggeststhat women-oriented sustainable consumption policies couldwork as a tool that municipalities and other urban actorscould use to reduce GHG emissions from households.

Among the approaches to mitigate GHG emissions inthe built environment applied over the last two decades, theemphasis has been on energy efficiency measures – both interms of technologies and initiatives to reduce demand –with far fewer projects to reduce GHG emissions throughalternative forms of energy supply and limited evidence ofother initiatives targeting resource use. Initial climate

Cities are also experimenting withalternative forms ofrenewable and low-carbon energysupply


Box 5.6 Sustainable and affordable houses for the poor in Bishnek, Kyrgyzstan

A project developed by the Habitat Kyrgyzstan Foundation has provided more than 48 afford-able environmentally sustainable homes for low-income families using a traditional cane reedand clay construction technology. Heating is provided by an innovative coiled-circuit under-floorheating system. The houses meet local building regulations, but allow families to save up to 40per cent of the construction costs compared with conventional brick housing. The use of volun-teer labour further reduces the cost of the houses, and low-cost housing loans help to ensureaffordability.

The use of traditional building methods and locally available materials relies on therevival of a traditional cost-effective building technology commonly used during the 19thcentury, but replaced during the 20th century by brick building. The Habitat KyrgyzstanFoundation has adapted the traditional cane reed construction method to include a timberframe with cane reed and clay wall sections, improving insulation without compromisingcomfort.

Source: www.worldhabitatawards.org, last accessed 18 October 2010

Table 5.5

Costs and benefits of aproject to install200,000 solar waterheaters in the residential sector inYinzhou, China

Benefits

Climate benefits: Abatement of 88,900 tonnes of CO2eq per annum, 1.3 million tonnes over 15 years.

Other environment effects: Reduction of sulphur dioxide, nitrogen oxides, other air pollutants and wastes.

Economic and social effects: Potential health improvement. Low-cost water heating supply.

Costs

Subsidy:a US$1.28 million.Estimated gross financial costs:b 400 million RMB (US$48 million).Administrative, institutional Transaction costs likely to reach US$2 per heater to meet the need for and political considerations: advertisements and a good distribution system (US$0.4 million).The cost of certified emission Approximately US$1.3 per tonne CO2eq.reductions:

Notes: a Subsidy is calculated as the amount necessary to cover the cost differential between the solar water heater andthe electric water heater for the first five years, including the electricity cost reduction.b Gross financial costs here refer to the total cost of initial purchase and installation. The price of residential electricityadopted here is 0.65 RMB (US$0.08) per kilowatt hour (kWh).

Source: adapted from Zhao and Michaelowa, 2006

change action within the built environment has focused oneasy gains from energy and water efficiency, and the adapta-tion of existing technologies.62 The combination ofregulation, civil society action and the inclusion of sustain-able building principles could have a big impact uponincorporating climate change mitigation technologies andprinciples within new buildings. Yet, there are obstacles toretrofitting existing buildings, such as inadequate returns oninvestment, difficulties in dealing with existing stock, lack offinancial incentives and regulatory constraints, dependencyupon occupancy cycles, and general lack of informationabout available technological solutions. The combination ofsocial and environmental benefits that energy efficiency cangenerate is particularly relevant in developing countries,where environmental measures may tackle other socialproblems such as ‘fuel poverty’. However, there is a case tolook beyond these measures as their impact may be reducedby the ‘rebound effect’ – that is, the tendency to useefficiency gain to increase consumption.63 In this context,energy efficiency measures need to be coupled with those todevelop low-carbon renewable energy sources and the reduc-tion of energy demand.

Urban infrastructure

Urban infrastructure – in particular, energy (electricity andgas) networks, and water and sanitation systems – is criticalin shaping the current and future trajectories of GHGemissions. The type of energy supply, the carbon intensity ofproviding water, sanitation and waste services, and therelease of methane from landfill sites are important, thoughoften hidden, components of GHG emissions at the locallevel. Infrastructure systems frequently lie outside the directcontrol of municipal governments, are intertwined withpower struggles over the rights of those living in informalsettlements,64 and require significant resources and long-term planning. The significant upfront costs of renewing orreplacing existing infrastructures, or of providing suchsystems to the expanding areas of cities, means that invest-ment in infrastructure is often delayed in favour of morepressing immediate concerns. Furthermore, although urbaninfrastructure systems are often regarded as gender neutral,men and women are affected differently by water, waste andenergy policies as their work and community roles differ. Forexample, while women are often responsible for ensuringenergy supply at the household level, they may be excludedfrom technical work on the energy systems, often regarded

as a male domain.65 Equally, women’s safety and securitymay be more dependent on adequate infrastructure systems,such as the provision of adequate lighting and sanitationfacilities.66 Urban infrastructure systems therefore poseunique and complex challenges for mitigating climatechange.

At the same time, the very nature of urban infrastruc-ture systems is changing significantly. In developed countries,research has documented the demise of the nationallyintegrated, ‘modern’ homogeneous utility networks in theface of processes of market liberalization, privatization, neo-liberal political ideologies, shifts in urban planning, newtechnologies and new practices of consumption, leading tothe ‘splintering’ of urban infrastructure systems.67 Similarprocesses, although often less apparent, are taking place incities in developing countries. Thus, across a diverse range ofcities, a sense of social, political and technical dynamism andinstability now characterizes the provision of basic servicesand infrastructure development. Within this context,mitigating climate change is becoming an important issue,but one that competes for attention with other pressures forenergy security and affordability, and the provision of basicservices. Nonetheless, municipal authorities – together withother government, private and civil society actors – haveundertaken a range of schemes in order to reduce GHGemissions through the refurbishment and development ofurban infrastructure systems (see Table 5.6).

Of the three infrastructure areas considered in thissection, research suggests that initiatives to explicitlyaddress climate change have been concentrated in theenergy and energy-from-waste domains and on the provisionof new forms of energy supply, with fewer initiatives toaddress the carbon intensity of the provision of water, sanita-tion and waste services or to reduce demand. In some citiesin developing countries, the Clean Development Mechanism(CDM)68 has been an important driver of infrastructureprojects, particularly landfill gas capture (see discussionbelow). Issues of energy security have also been importantdrivers for the development of low-carbon energy supplysystems in developing countries and initiatives for demandreduction in some Latin American and African cities. InIndia, cities such as Chennai have been successful inpromoting rainwater harvesting as a form of water conserva-tion. In Latin America, concerns for water security are alsoleading to the development of initiatives with benefits formitigating climate change. While urban infrastructure initia-tives are often led by municipal governments or urban utilityauthorities, regional and national governments, internationalagencies and private companies are frequently involvedbecause of the multilevel nature of such systems.

In terms of energy systems, three differentapproaches for developing low-carbon forms of urban energysupply can be identified. First, many municipalities havesought to reduce the carbon footprint of existing supplynetworks. An increasingly common initiative, found in citiessuch as Melbourne (Australia), Beijing (China) and Jogjakarta(Indonesia), has been to retrofit street-lighting systems withenergy-efficient bulbs. Cities, particularly in Europe, havealso sought to develop existing district heating and combined

Municipal authorities … haveundertaken a rangeof schemes in orderto reduce GHGemissions throughthe refurbishmentand development ofurban infrastructuresystems

In some cities indevelopingcountries, the CleanDevelopmentMechanism (CDM)has been an impor-tant driver ofinfrastructureprojects



Alternative energy supply: Development of renewable energy or low-carbon energy supply systems at the city scale.

Landfill gas capture: Use of gas produced by landfill sites for energy provision.Alternative water supply: Use of alternative forms of water supply, storage and processing to reduce

energy use at city scale.Collection of waste for Development of alternative collection systems and ways of using waste to recycling or reuse: reduce methane produced at landfill sites.Energy and water Enhancing the efficiency of existing infrastructure systems or development efficiency/conservation: of new efficient systems.Demand reduction: Schemes to reduce demand for energy and water use, and for the collection

of waste.

Table 5.6

Climate change mitigation and urbaninfrastructures

heat and power (CHP) plants. In Germany, Berlin is home toWestern Europe’s largest urban heat network, with over1500 kilometres of pipes and over 280 district-level CHPplants stretching across the city, delivering low-carbonenergy to a wide variety of consumers.69

A second approach has been for municipalities topurchase renewable energy, either for their own buildingsand operations, or as a means of offering consumers accessto green energy at a reduced cost. This approach is oftenfacilitated by purchase agreements between the municipalityand a private supplier of low-carbon or renewable energy,such as in the case between Cape Town and the DarlingWind Farm in South Africa, or the commitment of the City ofSydney (Australia) to achieve the supply of 100 per cent ofthe city’s energy from renewable sources by using a systemto accredit private energy companies.70

A third approach has been to develop new low-carbonand renewable energy systems within cities. In these initia-tives, climate change mitigation is often expressed as asecondary objective in relation to ensuring energy security.This is the case in the growing interest of Latin Americancities such as Quito (Ecuador), Bogotá (Colombia) and Rio deJaneiro (Brazil) in sources of energy that may reduce theirdependence on oil by promoting the use of natural gas inhouseholds. In Cape Town (South Africa), the companyEskom, backed by the national government, has proposedthe construction of a nuclear plant to meet the twin objec-tives of guaranteeing the energy safety of the region andreducing the city’s carbon emissions; but the project hasfound considerable local opposition from both the City ofCape Town and diverse stakeholder groups, mirroring globaldebates about the role of nuclear power in climate changemitigation.71 In China, the Beijing municipal government hasaccelerated the development of clean energy sources, includ-ing geothermal resources, biomass and wind power. Inaddition to the 118 plants already in operation by the end of1998, 174 new geothermal wells were constructed between1999 and 2006. Beijing now consumes about 8.8 millioncubic metres of geothermal water each year, reducing CO2emissions by 850,000 tonnes during the period of 2001 to2006.72 Beijing is also increasingly looking at wind powerand biomass generation, and the city had planned to increasethe energy share of these renewable energy sources to 4 percent by 2010. The Guanting wind farm, located on thesouthern bank of the Guanting Reservoir, is Beijing’s firstwind power generation station, with 33 wind turbinescapable of generating 49.5MW of electricity per year.73 Itwas completed in January 2008 as a CDM project.

While investment of the scale and ambition displayedby Beijing is difficult to imagine for the vast majority ofmunicipal authorities, national and international drivers,together with partnerships with private-sector companies,are leading to a growing emphasis on renewable and low-carbon energy systems. For example, the US Department ofEnergy has established a partnership with 25 cities todeliver Solar American Cities. The cities selected willreceive a combined US$5 million of funding from thedepartment plus hands-on technical assistance over twoyears. In Boston, for example, the goal is to achieve 25MW

cumulative installed solar capacity by 2015.74 Although thecosts of solar energy in the US are high, in Boston itsadoption may be facilitated by the high local energy prices,and the municipality is due to remove some market barrierssuch as in urban planning charters, zoning regulations,building codes, permitting and inspections, coupled withcity-level solar incentives such as solar rebates, financialassistance or tax credits. At the international level, theCDM has the potential to be an important driver for energy-from-waste projects in developing countries, includingAterro Bandeirantes and Aterro San Joao in São Paulo(Brazil); the Zámbiza landfill methane plant in Quito(Ecuador); the Bordo Poniente landfill biogas capture plantin Mexico City; and – in South Africa – the Bellville Southlandfill site in Cape Town and the gas-to-energy project inJohannesburg. While such schemes are frequently regardedas ‘technical’ fixes, there is evidence that they can be usedto address broader social issues and may offer significantopportunities for the empowerment of women who workon the lower end of the waste chain (see Box 5.7).

Schemes to generate energy from waste have alsoproven popular in developed countries where private-sectorcompanies have frequently provided the finances for munici-pal schemes. In Dallas (US), an interstate ‘green’ gas saleagreement will allow Dallas Clean Energy LLC to sell bio-methane captured at McCommas Bluff Landfill to ShellEnergy North America.75 The initiative Human Waste toPower the City, announced in June 2009 in Manchester(UK), is a UK£4.3 million two-year demonstration scheme,initiated by National Grid and United Utilities,76 to converthuman waste into bio-methane to power 500 homes.77

However, despite these initiatives and the increasing interestin waste to energy, research suggests that, beyond small-scale demonstration projects,78 the development oflow-carbon energy systems remains a low priority in cities.79

Outside of the energy sector, and beyond the growinginterest in generating energy from waste, there is relativelylittle evidence that municipalities are linking policies for

The CDM has thepotential to be animportant driver forenergy-from-wasteprojects in developing countries

Schemes to generateenergy from wastehave also provenpopular indeveloped countries


Box 5.7 Feminist action to gain recognition for women waste pickers in Mumbai, India

The Parisar Vikas (eco-development) programme was launched in 1998 by the Stree MuktiSanghatana (Women’s Liberation Organization), established in 1975, with the cooperation ofthe Municipal Corporation of Greater Mumbai. The programme aims to address the problemsof waste management and of self-employed women engaged in the ‘menial’ tasks of collectingwaste.

The action twins the objectives of improving the social status and economic situation ofwomen waste pickers in Mumbai and recognizing their potential role in achieving the goal of a‘zero waste’ Mumbai. In parallel with activities to achieve the active liberation of women wastepickers (such as the organization of training programmes, the arrangement of day-care centres,facilitating their access to health and educational programmes for their children, counsellingcentres and the development of cultural events which display the reality of these women), StreeMukti Sanghatana is now collaborating with staff at the Baba Nuclear Research Centre to trainwomen in composting, maintenance of biogas plants and fine sorting, and to involve womenwaste pickers in the operation of a pilot methane gas generation facility.

Source: Mhapsekar, 2010; see also www.streemuktisanghatana.org, last accessed 18 October 2010

recycling and reducing waste directly to climate change.However, in Nigeria, the Lagos State Waste ManagementAuthority argues that although African cities have compara-bly less GHG emissions than cities in the developed world, agreat portion of these emissions can be attributed to wastemanagement issues. Thus, they expect that their ongoingstrategies to improve waste transport planning and themanagement of landfills, as well as their campaign to reducethe private burning of refuse, will have positive impactsupon the reduction of Lagos GHG emissions.80 Besidesbetter management, education and awareness initiativeshave been demonstrated to be effective in reducing thecontribution of landfill sites to GHG emissions, as in theexample of Yokohama (Japan) (see Box 5.8). However, suchinitiatives to reduce the amount of waste sent to landfill mayparadoxically weaken the viability of current and futureenergy-from-waste plants, which rely on a secure stream ofwaste as a fuel. The potential conflicts between ‘technical’and ‘behavioural’ approaches to reducing GHG emissionsfrom landfill highlight the dilemmas facing urban mitigationefforts where the impacts of policies and measures areuncertain and the benefits and costs of action are dividedacross a number of different stakeholders and communities.

Initiatives which specifically aim to reduce the carbonintensity of water and sanitation systems at the urban levelare also rare. One example is in Mexico City, where theupgrade of network infrastructure will include the upgradeof 2300km of damaged networks and the establishment of336 separate hydrometric sectors to facilitate the detectionand repair of leaks. These actions will require the investmentof 2970 million pesos (US$240 million) and may save up to45,500 tonnes of CO2eq/year.81 In addition, there is aninnovative proposal to generate energy from the flows ofwater in the network, similar to that under consideration inDurban (South Africa).82 It is estimated that this measurealone could reduce the city’s emissions by 40,700 tonnesCO2eq/year.83 While the viability of such innovativemeasures will depend on the particular characteristics ofwater supply systems, the potential GHG emissions savingsthat could be achieved through these sorts of maintenance,

modernization and efficiency measures that are alreadytaking place in many cities may be substantial.

In summary, initiatives in the urban infrastructuredomain have focused on energy efficiency schemes, prima-rily driven by concerns for energy security and financialsavings. While such projects are politically and economicallyattractive, they may fail to deliver long-term GHG emissionssavings as initial reductions in energy use may be limited bythe ‘rebound effect’ as demand for energy continues togrow. However, with limited evidence of mitigation initia-tives in terms of the development of renewable energysystems – or in the water, sanitation and waste sectors – akey finding from this analysis is that there may be significanthidden potential to mitigate climate change at the urbanlevel through infrastructure networks.

Nevertheless, there remain substantial barriers to therealization of these mitigation gains, not least in terms of theeconomics and politics of renovating existing infrastructuresystems, building new networks, and meeting the basicneeds of urban communities, particularly those in informalsettlements. Few of these projects address social inclusionissues explicitly, or appear to specifically target low-incomegroups, disadvantaged areas or slums. In some cases, socialinclusion concerns have been at least acknowledged – inanticipation of potential social conflicts generated by thesemeasures – as is the case of the landfill gas to energy projectin Johannesburg (South Africa), which will include a publicconsultation before its completion. In general, however,urban infrastructure projects rely on the assumption that anyimprovements on current infrastructures will be beneficialfor all the inhabitants of the city, an assumption that requirescritical scrutiny as climate change tends to deepen the exist-ing inequalities amongst urban populations in terms ofaccess to basic services.

Transport

The transport sector is a significant contributor to GHGemissions, representing 23 per cent (worldwide) and 30 percent (OECD) of CO2 emissions from fossil fuel combustionin 2005.84 In developing countries, especially China, Indiaand other Asian countries, although transport’s share ofGHG emissions is low, it is growing much faster than othersectors.85 One of the key reasons for this rising trajectory isthe challenge of urban sprawl, discussed above; but thegrowth in GHG emissions from the transport sector alsorepresents the widespread modal shift that is taking place incities in developing countries as household incomes and theaffordability of motorized individual transport increases andaspirations for such forms of mobility, at both an individualand municipal level, increase. Moreover, urban sprawl mayincrease the demand for travel in ways that may not be easilymet by public transport.86 For example, ‘the transport sector… [is] the “carbon time bomb” ’ in Yogyakarta (Indonesia), as‘the fastest growing fossil fuel consuming sector in thecity’87 in part because ‘non-motorized transport modes suchas the “becaks” (peddycabs) have been banned’ due to theirperception as being insufficiently ‘modern’ for municipalaspirations for the city.88

Energy efficiencyschemes … may failto deliver long-termGHG emissionssavings as initialreductions in energyuse may be limitedby the ‘reboundeffect’

In developingcountries …although transport’sshare of GHGemissions is low, itis growing muchfaster than othersectors


Box 5.8 Raising public awareness for waste reduction in Yokohama, Japan

Yokohama’s success in waste reduction is attributed to the city’s public awareness campaignsand the active participation of stakeholders in the city’s ‘3R’ activities (i.e. reduce, reuse andrecycle). In 2003, Yokohama launched its G30 Action Plan to reduce waste by 30 per cent by thefinancial year 2010, using waste quantities from the financial year 2001 as baselines. Apart fromattributing responsibilities for waste reduction to all stakeholders, the plan also includesenvironmental education and promotional activities, such as 11,000 seminars forneighbourhood community associations to explain waste reduction methods, 470 campaigns atrailway stations and 2200 awareness campaigns at local waste disposal points.

The waste reduction target of 30 per cent was achieved in 2005, and by 2007 waste hadfallen by 38.7 per cent relative to 2001 figures. The reduction in waste from 2001 to 2007 isequivalent to 840,000 tonnes of CO2 emissions. The scheme also had economic benefits,including US$23.5 million from selling recyclables and US$24.6 million from electricity gener-ated from waste incineration.

Source: Suzuki et al, 2009

However, the growth of private transport is notgender neutral. A Swedish survey from 2007 showed that 75per cent of all cars were owned by men; moreover, women’scars are generally smaller (thus, generally emit less) thanthose owned by men.89 In the UK, 27 per cent more menthan women hold driving licences, and women are 38 percent more likely not to have access to a car, as well as twiceas likely to be a non-driver in a household with a car.90 In theUS, men constitute two-thirds of long-distance commuters,while women tend to become dependent on and favourablyinclined to using public transport.91 Perhaps because of theirlesser dependence on private transport92 it has beensuggested that women may be more willing than men toaccept policies and measures that restrict cars.93

At the same time, as the proportion of journeys madein cities by cars and other forms of personalized motorizedtransport increase, so do the challenges of congestion and airpollution. The synergy between mitigating climate changeand these twin issues that are both highly visible in the cityand which have popular support has meant that the transportsector is one in which a range of schemes have been devel-oped to reduce GHG emissions (see Table 5.7).

Evidence suggests that there is a contrast betweenareas where the transport sector features quite prominentlyin climate change plans and initiatives (such as in Europe and

Latin America), and areas where the transport sector hasreceived considerably less attention than other sectors, suchas energy infrastructure and the built environment (i.e.North America, Australia and New Zealand).94 Cities indeveloping countries show a growing interest in the develop-ment of new public transport infrastructure and technicalinnovation, such as programmes for the introduction of newtechnologies, fleet replacement with energy-efficientvehicles and fuel switching. Because of the significant invest-ments in infrastructure and technology involved, initiativesto reduce GHG emissions in the transport sector frequently


Box 5.9 Congestion charges: Past, present and future

Congestion pricing is a system of charging road users a fee for using the road in certain areas at certain times. It has been introduced in anumber of large European cities, such as Milan, London, Rome and Stockholm, with the aim of reducing inner-city traffic volumes, reducing airpollution and encouraging the use of more fuel-efficient and environmentally friendly vehicles. Generally, congestion charges apply upon enter-ing a clearly demarcated urban area and are paid on either a daily or per trip basis using a range of methods (online, mobile phone textmessage, swipe cards, scratch cards or by sensors installed in cars). Sometimes they are adjusted to the time of day, traffic levels or type ofvehicle, and usually include some form of exemption for residents, low-emission vehicles, public transport and two-wheeled motorized trans-port.

The first congestion charge system was introduced in 1975 in Singapore and was combined with car ownership restraints. Initially itwas not linked with climate change, but focused on concerns about traffic congestion.

In Rome (Italy), the ‘limited traffic zone’ was set up in 2001 to improve mobility and limit private vehicle trips in the historic citycentre. Around 250,000 vehicles (12 per cent of registered vehicles in Rome) were permitted inside the area, resulting in a 10 per centdecrease in traffic volumes overall, a 20 per cent decrease during the restriction period (06.30am to 18.00pm) and a 6 per cent increase inpublic transport use.

In Milan (Italy), arguably Europe’s third most polluted urban centre, more than half of citizens use private cars and motorcycles, whichled the mayor of Milan to introduce ‘ecopass’ in 2008. This is a pollution-adjusted congestion charge affecting the 8 square kilometre citycentre (5 per cent of the city’s total area), levied on a sliding scale of engine types (between 07.30am to 19.30pm on weekdays).

In the UK, the London Congestion Charge Zone, one of the largest in the world, was introduced in Central London in 2003 andextended to some parts of West London in 2007. A daily charge of UK£8 allows drivers to enter the 21 square kilometre zone (07.00am to18.30pm on weekdays). This resulted in traffic volume reductions of 18 per cent at peak times (15 per cent overall); a traffic delay reductionof 39 per cent; increased cycling by 20 per cent; and a 20 per cent increase in taxi and bus use. It should be noted that this success has notbeen the case across the UK; a similar scheme established in Manchester has not achieved the same results.

In Stockholm (Sweden), congestion fees were implemented on a permanent basis in 2007. These are levied every time a user crossesthe cordon area, with the charge varying over the day according to the congestion levels (highest during morning and afternoon peaks,moderate during the middle of the day, and zero during nights and weekends). This scheme has resulted in an overall traffic reduction of 25per cent; a waiting time reduction of 30 per cent; and a 50 per cent reduction in traffic volume during the evening rush hour.

Overall, evidence of the success of these schemes has been positive and the initial public resistance seems to have waned followingtheir implementation. There have been many implementation problems, especially surrounding the initiation of the schemes. These includeresistance from stakeholders and citizens, a lack of alternative infrastructure and problems with payment operations. Some questions aboutthe economical results of the congestion charge in London have also been raised.

Sources: Prud’homme and Bocarejo, 2005; Leape, 2006


New low-carbon transport The development of new transport infrastructure to encourage infrastructure: low-carbon modes of transportation.Low-carbon infrastructure The renewal or upgrading of transport infrastructure to reduce GHG renewal: emissions.Fleet replacement: Replacement of vehicle fleet with energy-efficient or low-carbon vehicles.Fuel switching: Switch from the use of fossil fuels for powering fleet to alternative low-

carbon or renewable fuels.Enhancing energy efficiency: Measures to enhance the energy efficiency of existing vehicles and

their use.Demand-reduction measures: Measures aimed at reducing the demand for individual motorized

transport.Demand-enhancement Measures aimed at enhancing the demand for alternative forms of travel measures: (e.g. public transport, walking and cycling).

Table 5.7

Climate change mitigation and transportation

The growth ofprivate transport isnot gender neutral

depend on partnerships with private-sector organizations aswell as the involvement of national and regional govern-ments. Interventions by grassroots organizations orindividuals in the transport sector are normally limited toprojects for the promotion of non-motorized transport anddemand management initiatives, such as car-sharingschemes.

A recent survey of climate change plans in 30 citiesworldwide found that the most common climate changemitigation actions in transport were the development ofpublic transport, the implementation of cleaner technolo-gies, the promotion of non-motorized transport, publicawareness campaigns and the implementation of cleanertechnologies.95

Regulatory measures to manage demand – such asphysical restraint (e.g. those implemented in Mexico Cityand São Paulo, Brazil), parking restraints, establishment oflow emissions zones (implemented in Beijing, China, andseveral European cities) and speed restrictions – appear tobe less common, with few examples of economic incentivesbeing used. The examples discussed here also suggest thatmunicipalities have a key role in the provision of infrastruc-ture and the development of new technologies, and that theyuse a wide range of regulatory tools, including mandatorystandards and targets, planning law or planning guidance,performance evaluation and the ban of certain fuels,together with some financial instruments such as subsidies,loans to modernize the fleet and taxes, such as congestioncharges (see Box 5.9).

Turning first to issues of transport infrastructure, themitigation of climate change is one driver behind the devel-opment of new mass transportation infrastructure. One ofthe most common initiatives is the operation of bus rapidtransit (BRT) systems, guided bus lines or bus ways toimprove the quality and speed of bus services. BRT andsimilar initiatives – which in many cases may be imple-mented at a fraction of the cost of an underground metrosystem – already exist or are planned in cities in all majorregions of the world, although not all these initiatives arespecifically tied with climate change mitigation objectives(see Table 5.8). The Transmilenio BRT System in Bogotá(Colombia) is often mentioned as a leading example,although it follows the pioneering experience of Curitiba(Brazil).96 The service, opened in 2000, is administered by

Transmilenio S.A., a public company, and operated by privatecontractors. The system consists of 84km of central bus linesconnected with 515km of peripheral lines and 114 passen-ger-picking stations, and can transport up to 1 millionpassengers every day. In addition, its 9000 buses are to be replaced with energy-efficient models. However,Transmilenio has been criticized for being overcrowded, tooexpensive, slow and offering limited access to certain areasof the city. Nevertheless, the experience of Bogotá is oftenmentioned in other cities as an example of actions to extendor improve existing mass transportation systems. Otherpublic transportation systems such as trams or trains mayhave received less attention in climate change mitigationplans because of their high costs; but the use of CDM creditsmay increase the number of these types of projects in devel-oping countries. For example, the Egyptian Ministry ofTransport and the National Authority for Tunnels, in coopera-tion with CDM-Egypt, are planning to build a third line forthe Greater Cairo Metro Network between 2010 and2031.97 The project will cost €856 million and it is expectedto be funded by CDM credits.

A second area in which municipalities have sought totake action is through the development of low-carbonvehicles and fuels. In Germany, Hamburg and Berlin haveteamed up in the Clean Energy Partnership,98 which foreseesthe development of public fuel cell buses and urban hydro-gen filling stations. In Hamburg the aim is to have 10 fuelcell buses in operation by 2010, 500 to 1000 fuel cellvehicles by 2015, together with a public network of fillingstations. In Rome (Italy), the urban public agency in chargeof local public transport services and the Commune of Romehave been involved in the introduction of over 80 electricallypowered buses and 700 methane buses. Stockholm(Sweden) has the largest green fleet in Europe, and isheading for 100 per cent renewable energy in public trans-port by 2010, with tram and rail being powered by wind andhydroelectricity, and ethanol and biogas fuels used in a largeproportion of the city’s own fleet, as well as private vehicles(35,000 in total, about 5.3 per cent of vehicles) reducingCO2 emissions by 200,000 tonnes annually. Significantly,cities are also providing arenas for the experimentation andpromotion of new technologies, such as in the cases ofcompressed natural gas use in transport in several citiesaround the world including Tehran (Iran), Mumbai (India),

Initiatives to reduceGHG emissions inthe transport sectorfrequently dependon partnerships withprivate-sector organizations

The mitigation ofclimate change isone driver behindthe development ofnew masstransportation infrastructure


Region Number of Examplescities Name City Status

Developed countriesEurope 21 Ipswich Rapid Ipswich, UK In operation since 2004North America 52 Rapid Ride Albuquerque, US In operation since 2004

Super Loop San Diego, US In operation since 2009Other 6 O-Bahn Busway Adelaide, Australia In operation since 1986

Northern Busway Auckland, New Zealand In operation since 2008Developing countriesAfrica 8 Lagos BRT Lagos, Nigeria In operation since 2008

Rea Vaya Johannesburg, South Africa In operation since 2010Asia and the Pacific 59 Transjakarta Jakarta, Indonesia In operation since 2004

Transit Metrobus Istanbul, Turkey In operation since 1994Latin America and the Caribbean 30 Trolmerida Mérida, Venezuela In operation since 2007

Rede Integrada de Transporte Curitiba, Brazil In operation since 1980

Table 5.8

Bus rapid transit (BRT)systems planned or inoperation in differentregions

Dhaka (Bangladesh) and Bogotá (Colombia),99 while in Brazilbiofuels are promoted in the country’s megacities.

A third set of initiatives in the transport sectorincludes demand-reduction and demand-enhancementmeasures, led by a wide range of actors and involving differ-ent policy instruments, modes of transport andunderstandings of mobility. For example, a non-profit organi-zation launched by transportation activists, Car Share, haslaunched City Car Share schemes in several US cities such asSan Francisco, Oakland and Berkeley. Public bicycle sharingnetworks allow people to borrow or rent bicycles so thatthey can travel around the city without having to own abicycle, reducing individual purchase and maintenance costs,and storage space requirements. Such programmes arepopular in European cities and are used, amongst others, inBarcelona, Spain (Bicing); Milan, Italy (Biciclette Gialle);Paris, France (Velib); Rome, Italy (Romainbici); andStockholm, Sweden (Stockholm City Bikes). A similarprogramme also exists in Montreal, Canada (Bixi).Municipalities may also impose traffic restrictions, such ascongestion charges (see Box 5.9), although this may reducethe access to the city to social groups who cannot affordsuch tax.

Municipalities can also work with other institutionsto reduce demand. For example, the City of Cape Town(South Africa) has a project to develop partnerships withthe largest employers within the city to reduce the work-related mobility needs of their employees. However, theintroduction of demand management measures is notalways straightforward. For example, in Brazil, the PortoAlegre Charter to facilitate and promote pedestrian mobilitywithin the city – which gave new rights to pedestrian anddisabled people – had to be substantially modified before itcould obtain the approval of local representatives in 2007,although the original proposal of shifting the right of wayfrom motorized vehicles to pedestrians could be main-tained.

The dynamism of the transport sector and its interac-tion with other sectors makes it difficult to anticipate theconsequences and future of climate change mitigationmeasures, particularly when climate change mitigation plansand actions are confronted with the increasing mobilitydemands of the urban population. Measures to control andreduce demand need to be complemented with alternativesfor mass transport and non-motorized transport that oftenrequire significant investments in new infrastructure. Inmany cities, climate change mitigation concerns have beenpreceded by concerns about urban congestion and air quality,which makes transport a central issue in urban planning andmanagement. Recent transport studies suggest that differen-tial prices of energy sources, based on carbon content, couldhelp to promote better urban transport efficiency.100 Yet, it isnot clear how this could be implemented at the city level. Onthe other hand, the combination of improved car technolo-gies and traffic management may complement carbon pricingto mitigate climate change while improving the sustainabilityof current urban transport systems.101

Carbon sequestration

In addition to reducing the amount of GHG emissions thatare produced in the city, one means through which urbanactors could address the challenge of mitigation is throughcarbon sequestration. Carbon sequestration involves remov-ing GHG emissions from the atmosphere, either throughenhancing natural ‘carbon sinks’ (e.g. conserving forestedareas and enhancing river environments), the developmentof new carbon sinks (e.g. reforestation or afforestation) orthrough the capture and storage of GHG being producedwithin the city. The capture of methane from landfill sites forenergy generation102 is also a form of carbon sequestration.Traditionally, such activities have been peripheral to themain focus of urban mitigation activity. However, new devel-opments in carbon capture and storage technologies,growing interest among national governments in carboncapture and storage, especially in developed countries andthe more industrialized developing countries, and theincreasing availability of carbon finance through interna-tional policy instruments – such as the CDM – are makingcarbon sequestration schemes more popular at the urbanlevel (see Table 5.9). Regionally, carbon sequestrationschemes are more common in developing country cities,often associated with gaining CDM credits or developmentprogrammes. However, it should be noted that actionspromoting urban tree-planting and restoration, preservationor conservation of carbon sinks may be taken in cities indeveloped countries for reasons of environmental protectionor the preservation of urban green spaces without associat-ing them specifically with climate change mitigationobjectives.

Urban carbon sequestration, however, is still in incipi-ent stages. The technology to facilitate carbon capture andstorage is still under development, and proposals for itsimplementation in cities are only now emerging (see Box5.10). Carbon offset schemes based at the city level are alsorare and often reach beyond city limits. In the US,Philadelphia Zoo (in partnership with private actors) has initi-ated the Footprints scheme to green zoo operations, developlocal and international carbon offset projects, and engagewith communities in Philadelphia and beyond. The Footprintsscheme includes two reforestation projects, one in a formerscrub site close to the zoo and another in Sukau, Borneo(Malaysia). Offsetting projects are often led by individuals orNGOs; but sometimes governmental authorities may have acrucial role in mediating the schemes. For example, since2008 the city of Rio de Janeiro (Brazil) has created its own‘carbon market’, which facilitates the participation of private

In many cities,climate changemitigation concernshave been precededby concerns abouturban congestionand air quality,which makes transport a centralissue in urbanplanning andmanagement

New developmentsin carbon captureand storagetechnologies … aremaking carbonsequestrationschemes morepopular at the urbanlevel



Urban carbon capture The development of schemes to capture CO2 emissions from energy and storage: generation within the city and place in long-term storage.Urban tree-planting Schemes which seek to plant trees to develop the urban ‘sink’ capacity programmes: for CO2.Restoration of carbon sinks: Schemes which seek to restore areas of natural carbon sinks in the city.Preservation and Schemes which seek to preserve and enhance areas of natural conservation of carbon sinks: carbon sinks in the city.Carbon offset schemes: The purchase of carbon sequestration offsets by actors within the city

from schemes located either in the city or elsewhere.

Table 5.9

Climate change mitigation and carbonsequestration

companies in carbon-offsetting projects by providing themwith a methodology for calculating the amount that they needto reforest in order to abate carbon emissions, a helpline, andcontacts with potential offset projects.

Most carbon sequestration initiatives at the urbanlevel relate to tree-planting schemes and the restoration andpreservation of carbon sinks. Urban tree-planting prog-rammes frequently rely on cooperation between municip-alities and citizens. This is the case in several cities in LatinAmerica where the municipality has developed technologytransfer and promotion campaigns for urban tree planting.However, the results depend largely on the voluntary andnon-monitored intervention of citizens – for example, theTree Planting Incentives in São Paulo (Brazil), the OneHouse, One Tree programme in Lima (Peru) or the Organic

Urban Gardens programme in Caracas (Venezuela). InJohannesburg (South Africa), the Greening Sowetoprogramme was intended to contribute to the preparationsfor the 2010 FIFA World Cup in addition to its carbonsequestration benefits. The programme started in 2006 withthe objective of planting 300,000 trees in Soweto.103

The preservation and restoration of carbon sinks isalso dependent on government intervention, For example, inLagos (Nigeria) and surrounding areas, a ban on tree fellinghas been imposed. So far, more than 3000 trees in the statehave been counted and tagged to prevent felling,104 althoughis not clear how the ban is enforced. In Bogotá (Colombia),the Botanical Garden – in partnership with local authorities– has started an initiative to improve and regulate urban treemanagement for the protection and conservation of urbantrees, and the creation of a tree registry that may help topreserve individual trees.105 Carbon sequestration can becombined with city beautification, particularly when a rangeof measures to create and protect green spaces and facilitatepublic access are combined, such as in the case of Singapore(see Box 5.11).

In developing countries, CDM mechanisms may helpto initiate afforestation and nature conservation programmeswith carbon sequestration benefits. In Egypt, for example,the Environmental Affairs Agency, in cooperation with CDM-Egypt, is developing a project (2007 to 2017) for theafforestation of 10km of road (0.5 million trees) around thering road of greater Cairo. The project, which will cost US$4million, is expected to contribute to the reduction of GHGemissions (100,000 tonnes of CO2eq per year) and to localsustainable development objectives. However, carbonsequestration programmes need to acknowledge the differ-ential impacts that such programmes may have in differentpopulation groups. Further work on the role of gender inurban greening is needed to understand the differentservices that urban green areas offer to different socialgroups and their roles in maintaining them.

Despite their current low profile, carbon sequestra-tion projects appear to be gaining ground in at least threeways. First, the development of carbon capture and storagetechnologies may lead to urban pilot projects, although thistechnology is heavily dependent on economies of scale andcarbon storage facilities, with the result that few cities arelikely to provide suitable locations. Carbon capture andstorage has also been criticized for failing to address the rootof the climate change problem in terms of the use of fossilfuels, and any decisions to locate carbon capture and storageplants in urban settings is likely to attract significant opposi-tion. Second, the CDM and growing carbon markets mayhelp to finance afforestation and nature conservationprogrammes in developing countries. It is important tohighlight that these programmes may simultaneously providecarbon sequestration functions while also protecting waterand soil resources that are crucial for the adaptation of citiesto the potential impacts of climate change (see Chapter 6).Third, the rapid proliferation of initiatives such as carbonmarkets or offsetting schemes suggests that these schemesmay have more prominence in the future, although often,they may transcend the spatial boundaries of the city.

Most carbon sequestration initiatives at theurban level relate to tree-plantingschemes and therestoration andpreservation ofcarbon sink


Box 5.10 The future of energy? Piloting urban carbon capture and storage in Rotterdam, The Netherlands

The Rotterdam Climate Initiative combines the city administration, the regional environmentalprotection agency (DCMR), the Port of Rotterdam, and the businesses in the port. It has set atarget of 50 per cent CO2 reduction by 2025 (compared to 1990), two-thirds of which is to beachieved by the use of carbon capture and storage technology. At present, CO2 is piped andsold to horticulturalists to stimulate plant growth. However, through the capture of emissionsfrom two new coal-fired power stations, the process will be scaled up from current volumes (ofaround 400,000 tonnes per year) to approximately 1 million tonnes per year.

Once carbon capture and storage technology is more fully developed (anticipated by2020 to 2025), around 20 million tonnes of CO2 per annum will be stored in depleted offshoreoil and gas fields. The scheme focuses explicitly on involving stakeholders from the early stagesof the projects by presenting a realistic and detailed project timetable and formal consultationprocedure for stakeholders, as well as making use of existing infrastructures.

However, carbon capture and storage has been criticized for not providing a long-termsolution to greenhouse gas (GHG) reduction due to its high costs and lack of development oftechnology. Pilot schemes such as in Rotterdam may help to elucidate whether carbon captureand storage can fulfil its low-carbon promise in an urban context.

Source: Van Noorden, 2008

Box 5.11 Planning for a Garden City in Singapore

Since the 1960s, a wide range of actors in both public and private partnerships have been devel-oping Singapore into a ‘Garden City’. The effort attempts to increase the aesthetic appeal of thecity, providing public open spaces and improving air quality, protecting carbon sinks and reducingthe urban heat-island effect. The key strategies to create a Garden City are:

• tree-planting on all roads, vacant land and new development sites;• providing adequate, attractive and accessible parks, including 3300ha of parks, as well as larger

parks, such as the 185ha East Coast Park along the coastal areas, and smaller parks, such astown parks and precinct gardens; over the next 10 to 15 years, Singapore aims to addanother 900ha of park space;

• linking parks and people by introducing park connectors such as green corridors for peopleto stroll, jog and cycle between parks; to date, Singapore has about 100km of park connec-tors, which is expected to triple to 360km by 2020;

• retaining natural heritage in four nature reserves which cover more than 3000ha, or 4.5 percent of Singapore’s land area;

• building ‘gardens in the sky’ by encouraging developers to incorporate green roofing.

Source: Singapore Urban Development Authority, 2009

Assessing the impact of urban climatechange mitigation initiatives

The above discussion suggests that many different initiativesto mitigate climate change are taking place in cities acrossthe world. Despite this, there is still relatively limited infor-mation about the individual and collective impact of thesemeasures, especially when they extend beyond municipalbuildings and infrastructure systems or involve behaviouralchange. Municipal networks, such as the CCP campaign,Climate Alliance and C40, have sought to develop indicatorsof their achievements.106 The CCP Australia programme, forexample, calculated that its 184 members achieved ‘4.7million tonnes [CO2eq] abatement – equivalent to over amillion cars off the road for one year’ as well as ‘A$22 millionsaved by councils and their communities through reducedenergy costs’.107 However, such figures have been limited bytheir reliance on self-reporting and the lack of a commonmethodology to enable comparison between different inter-national networks or with cities that lie outside of thesenetworks. One current initiative that may contribute tobuilding a more accurate picture of the impact of urbanclimate change measures is Project 2°, which aims to provide‘the first global, multi-lingual emissions measurementtoolset designed to help cities measure and reduce theirgreenhouse gas emissions 24 hours a day, seven days week,via the web’.108 Independent studies explicitly examiningthe stocks and flows of GHG in cities have also beenconducted.109 Yet, these analyses are focused on understand-ing historical and future trends rather than any directassessment of the impact of policies and measures that have been put in place. There is therefore a need for newresearch which applies these analytical approaches to theassessment of current policy measures. However, it shouldbe noted that the International Standard for DeterminingGreenhouse Gas Emissions for Cities – jointly launched bythe United Nations Environment Programme (UNEP), UN-Habitat and the World Bank at the World Urban Forum in Riode Janeiro in March 2010 – provides a common method forcities to calculate the amount of GHG emissions producedwithin their boundaries.110

Despite such new methodologies, more generalchallenges of assessing the impacts of policy interventions,the relatively short time-scales involved, and the fragmentednature of the data available, especially with regard to levelsand reductions of GHG emissions across urban communities,will remain. In this context, basic guidance about the poten-tial of different measures may be more useful than measuresof emissions reductions. For example, it is clear that system-atic efforts to shift from fossil fuel-based energy and trans-port systems through the use of low-carbon technologies arelikely to have a more significant impact upon reducing GHGemissions than small-scale short-term initiatives to improveenergy efficiency, which may be compromised by the

rebound effect once initial financial savings have beenachieved. However, in reaching the ‘low hanging fruit’ – thesectors offering GHG reduction costs that yield long-termreturns even without their participation in carbon markets –such schemes may have several additional benefits and act asa means of getting climate change on urban agendas. Figure5.1 highlights the waste, transport and buildings sectors asthe ‘low hanging fruits’ of urban GHG mitigations.

In short, decisions over which mitigation measures toadopt will be determined by the social, political andeconomic circumstances in individual cities and guided bythe weight given to climate change concerns, rather than byany absolute evaluation of their effectiveness (see Table5.10). The wide range of actions and the tendency to adoptpiecemeal rather than strategic approaches documented inthis section point to the multiple drivers and barriers toachieving climate change mitigation in the city. While indeveloped countries urban actors may be constrained byinstitutional factors and lack of public support or leadership,in developing countries there is often little incentive formunicipalities to mitigate climate change when they cannotaddress the basic needs of current populations. In the face ofthese challenges, the following sections elaborate upon themodes of governing that municipalities and other urbanactors have adopted to mitigate climate change and theopportunities and constraints that they have encountered.

Based on the discussion of the differences betweenproduction and consumption perspectives to the measuringof GHG emissions in Chapter 3, Table 5.11 provides a morespecific overview of mitigation activities – from each ofthese perspectives – that can stop or reduce the currentgrowth in urban GHG emissions.

Decisions overwhich mitigationmeasures to adoptwill be determinedby the social, political andeconomic circum-stances in individualcities and guided bythe weight given toclimate changeconcerns, ratherthan by any absoluteevaluation of theireffectiveness


Figure 5.1

The ‘low hanging fruits’ of urban GHG mitigation

Source: ICLEI, 2010, p9

Power

0A

bate

men

t co

st €

per

ton

nes

of C

O2e

q, 2

030

30

25

20

15

10

5

0

–5

–10

–15

–20

–25

–30

Iron and steel

Capital intensity € per tonnes of CO2eq 5 10 15 20 30

0

–5

ChemicalsPetroleum and gas

Forestry

Cement

Agriculture

WasteTransport

Buildings

75 80


Type of measure Examples Climate change benefits Additional benefits Limitations

Leadership • Renewable energy • Limited direct impact • Demonstrate commitment • Impact assessment is difficultdemonstration projects upon GHG emissions to climate action • Could be perceived as

• Education campaigns • Encourage action by others tokenisticNo or low upfront • Energy- and water-efficient • Limited impact upon • Short-term financial savings • Difficult to enforce and costs behaviour GHG emissions unless • Environmental education often involves changing

• Waste minimization sustained over the long term ingrained organizational and cultural practices

Cost effective • Energy- and water-efficient • Dependent on the scale • Short- to medium-term • Energy and water savings technologies and timeframe of measures financial savings can be limited by the

• Impacts can be monitored rebound effect• Address issues of resource

poverty and securityMultiple benefits • Travel demand-reduction • Dependent on the scale • Address multiple goals of • Assessment of impacts

measures and timeframe of measures sustainability and well-being, is difficult• Reforestation and • Provides opportunities for including air pollution, • Reliant on the involvement

conservation projects working with a wide range congestion, urban green and actions of othersof actors and gaining space, resource security • Climate change benefits may political support for and meeting basic needs be sidelined if they conflict climate change with other objectives

Deep cuts • Low-carbon and renewable • Large-scale projects may • Offer opportunities to • High upfront costs and long energy infrastructure have significant direct update infrastructure payback periodsprojects impact; small- and medium- networks, provide access • Usually reliant on external

sized projects can act as to services for poor sources of funding and catalysts for change communities and partnerships with other

• Provides opportunities for informal settlements public and private actors, working with a wide range which can be fragileof actors and gaining political support for climate change

Source: adapted from ICLEI Australia, 2008, p6

Sector What can stop or reduce the growth in urban GHG emissions?Production perspective Consumption perspective

Energy supply A shift to less GHG-emitting power generation and As in the production perspective, but also a greater focus on distribution; incorporation of electricity-saving devices; less consumption among high-consumption households; a shift an increase in the proportion of electricity generated to less GHG-intensive consumption.from renewable energy sources and its integration into the grid; carbon capture and storage.

Industry A shift away from heavy industries and from industry As in the production perspective but with an extra concern to to services; increasing energy efficiency within enterprises; reduce the GHGs embedded in goods consumed by residents and capture of particular GHGs from waste streams. to discourage consumption with high GHG emissions implications.

Forestry and N/A (as no emissions are assigned to urban areas). Encouraging less fossil fuel-intensive production and supply chains for agriculture food and forestry products; addressing the very substantial non-CO2

GHG emissions from farming (including livestock); forestry and land-use management practices that contribute to reducing global warming.

Transport Increasing the number of trips made on foot, by bicycle, As in the production perspective but with a stronger focus on on public transport; a decrease in the use of private motor reducing air travel and a concern for lowering the GHG emissions vehicles and/or a decrease in their average fuel consumption implications of investments in transport infrastructure.(including the use of vehicles using alternative fuels); ensuring that urban expansion avoids high levels of private motor vehicle dependence.

Residential/ Cutting fossil fuel/electricity use, thus cutting GHG emissions As in the production perspective but with an added interest in commercial buildings from space heating (usually the largest user of fossil fuels in reducing the CO2 emissions embedded in building materials,

temperate climates) and lighting; much of this is relatively fixtures and fittings.easy and has rapid paybacks.

Waste and Reducing volumes of wastes, and waste management that As in the production perspective but with a new concern to reduce wastewater captures GHGs. waste flows that arise from consumption in the city but contribute to

GHGs outside its boundaries.Public sector N/A (as no emissions are acknowledged). Governance that encourages and supports all the above; also a strong and governance focus on lowering GHG emissions through better management of

government-owned buildings and public infrastructure and services; includes a concern for reducing GHG emissions generated in the building of infrastructure and the delivery of services.

Notes: Based on the discussion of GHG emission drivers in Table 3.18.N/A = not available.

Source: based on Satterthwaite et al, 2009b, pp548–549

Table 5.10

Identifying and prioritizing climatechange mitigationactions

Table 5.11

Mitigating urban GHGemissions: Productionversus consumptionperspectives

URBAN GOVERNANCE FORCLIMATE CHANGEMITIGATIONAs the section above has demonstrated, municipal authori-ties and other actors have developed a range of strategiesand measures for mitigating climate change in differentpolicy sectors. Research suggests that the mechanisms whichurban actors use to develop and implement these initiativescan be grouped into distinct ‘modes of governing’.111 First,the section reviews the changing nature of urban governanceand the ‘modes of governing’ that public authorities andprivate actors use in order to address climate change.Alongside four modes of governing that have been identifiedwithin municipal governance – self-governing, provision,regulation and enabling – the growing importance of corpo-rate, donor and civil society actors means that (quasi) privatemodes of governing – voluntary, private provision andmobilizing – are also becoming important. The sectionreviews municipal and private modes of governing, in turn,considering the mechanisms and policy instrumentsinvolved, comparing their use in the five key policy sectorsdiscussed in the previous section, and their generalstrengths and limitations.

Modes of governing climate change mitigation

The term governance can be broadly understood in twodifferent ways. First, in a ‘descriptive sense, it refers to theproliferation of institutions, agencies, interests and regula-tory systems’ involved in managing societies. Second, in a‘normative sense, it refers to an alternative model’ for organ-izing collective affairs, frequently assumed to be based onhorizontal coordination between mutually dependent actorswhere governments may be one among many agenciesinvolved.112 While there have been many calls to develop‘good governance’ in a normative sense, this section focuseson analysing different forms of governance captured in thedescriptive definition of the term. Such new forms of gover-nance are thought to have emerged as a result of a ‘profoundrestructuring of the state’ evident in:

• ‘a relative decline in the role of formal government inthe management of social and economic relationships’;

• ‘the involvement of non-governmental actors in a rangeof state functions at a variety of spatial levels’;

• ‘a change from hierarchical forms of government struc-tures to more flexible forms of partnership andnetworking’;

• ‘a shift from provision by formal government structuresto sharing of responsibilities and service provisionbetween the state and civil society’; and

• ‘the devolution and decentralization of formal govern-mental responsibilities to regional and localgovernments’.113

Understanding the nature, potential and limitations forurban climate change governance involves considering thedifferent ways in which urban governments operate, as wellas recognizing the important roles played by a variety ofother public and private actors. In this context, research hasshown that a small number of distinct ‘modes of governing’are being employed to address climate change in the urbanarena.114 In terms of the modes of governing deployed bymunicipal authorities, four approaches appear to be impor-tant:

1 self-governing: the capacity of municipalities to governtheir own operations, estate and activities;

2 provision: the shaping of practice through the deliveryof particular forms of services and resources;

3 regulation: the use of traditional forms of authority suchas mandates and planning law, and the oversight andimplementation of regulation created at other levels ofgovernment;115 and

4 enabling: the role of municipalities in facilitating,coordinating and encouraging action through partner-ship with regional or national governments, private- andvoluntary-sector agencies, and through various forms ofcommunity engagement.

While municipal modes of governing climate change weredominant during the 1990s, more recently, new modes ofurban climate governance are emerging in which privateactors (such as foundations, development banks, NGOs andcorporations) and public agencies outside the local authori-ties (donor agencies, international institutions) are initiatingschemes and mechanisms to address climate change mitiga-tion activities in the city.116 Three approaches appear to begaining ground, which in some ways mirror those beingdeployed by municipal authorities:

1 voluntary: the use of ‘soft’ forms of regulation topromote action either within an organization oramongst a group of public and private actors, combiningfeatures of the self-governing and regulation modesdetailed above;

2 public–private provision of low-carbon infrastructuresand services, either in place of or in parallel to govern-ment schemes, including initiatives developed throughthe auspices of the CDM; and

3 mobilization, where private actors seek to engage otherorganizations in taking action, such as through educa-tion campaigns.

Each mode of governing relies on a different combination ofpolicy instruments and mechanisms, and may be more orless effective in mitigating climate change in the urbanarena. The following sections review municipal andpublic–private modes of governing in turn, assessing theiruse in different policy sectors as well as their strengths andlimitations for achieving reductions in GHG emissions.

Four modes ofgoverning … havebeen identifiedwithin municipalgovernance – self-governing,provision, regulationand enabling

New modes of urbanclimate governanceare emerging inwhich private actors… and publicagencies outside thelocal authorities …are initiatingschemes and mechanisms toaddress climatechange mitigationactivities in the city


Municipal governance

These four approaches of municipal governance – self-governing, provision, regulation and enabling – are notmutually exclusive; rather, municipalities tend to deploy acombination of these modes at any one time. This is indica-tive of the impact of state restructuring, where – rather thangoverning in a direct, hierarchical, manner – the task forstate authorities is one of ‘meta-governance’: of articulatingand combining different modes of governance.117 However,research suggests that the self-governing mode remains thedominant approach adopted by municipal authorities inresponse to climate change. While the self-governing modehas significant limitations in terms of the proportion ofurban GHG emissions that can be addressed (see Table5.12), it offers a visible and often short-term means throughwhich municipal authorities can demonstrate their commit-ment to climate change. In developed countries, self-governing and enabling modes have been dominant, whileinitiatives in developing countries are often based on theprovision of low-carbon infrastructures and services. Whileregulation is the least frequently used mode of governing, itis most common in the transport and urban developmentsectors, reflecting the roles of local authorities in controllingair pollution and land-use planning. The development of

climate change initiatives in the urban infrastructure sectorhas primarily relied on the provision mode of governing,while the enabling mode dominates in the built environmentand carbon sequestration policy sectors.

This analysis suggests that municipal governments aremaking use of a wide range of policy instruments and mecha-nisms in seeking to address climate change. Given thecross-cutting nature of climate change as a policy issue, it isperhaps not surprising to find that there is no single ‘recipefor success’ – with the demands of different policy sectors,as well as different national and local contexts, leading to a‘patchwork’ of approaches being adopted. However, thedominance of the self-governing and enabling modes and thelimited role played by regulation point to the underlyingchallenges that municipal governments face in seeking toaddress climate change. On the one hand, accounting for theimpact of regulation, provision and enabling measures – interms of GHG emissions saved, and the financial andadditional benefits accrued – is a complex task. In an erawhere municipal governments are required to audit theirachievements, such measures may be deemed economicallyand politically unfeasible. At the same time, moving thiscomplex policy issue into concrete actions beyond the areaswithin which they exercise direct control involves municipal-ities challenging the deeply ingrained relationship between


Mode of governing Policies and mechanisms Examples Advantages Limitations

Self-governing • Management of local • Investment in energy-efficient Self-governing measures are under the Self-governing measures can only address authority estate street-lighting direct control of the municipality and can a small proportion of urban GHG emissions.

• Procurement • Purchasing renewable energy provide quick, verifiable and cost-effective They may be limited to those that can for municipal buildingsbuildings means of reducing GHG emissions. provide a financial return within the

• Leading by example • Behavioural change They provide a means for municipalities to (short) time horizons of local governments.programmes for local demonstrate leadership and commitment authority staff to addressing climate change.

Provision • Operation of municipal • Investment in low-carbon The provision of low-carbon infrastructure Municipal capacity for providing low-carbon infrastructure systems transport systems such and services has potential for significant infrastructure and services is hampered by a lack

as BRT reductions in GHG emissions by changing the of finances, dependency on the terms and • Green consumer • Household energy surveys carbon intensity of utility provision and conditions of capital loans, and a limited remit for

services and subsidized renovation altering the choices available to providing energy, water, waste and transport. programmes provided by households and businesses across the city. In contexts where there is a lack of basic municipal authority The development of new low-carbon services, developing low-carbon networks is

infrastructure networks could improve unlikely to be a priority. In addition, the provision access to basic services and improve of infrastructure and services is only one factor livelihoods. shaping their use and may not lead to an overall

reduction in GHG emissions without additional measures.

Regulation • Taxation • Congestion charging schemes Regulative measures can provide transparent Regulative measures can be difficult to implement • Land-use planning • Requirement for renewable and effective means for reducing GHG because of concerns about their impact upon

energy technologies in new emissions from a variety of policy sectors. businesses or particular sections of the development They provide a level playing field for the community. Regulations are difficult to apply

• Codes, standards, etc. • Energy and water efficiency business community. They may also yield retrospectively (e.g. to existing buildings) and standards for buildings additional revenue, which can be invested governments are often reluctant to regulate

in additional low-carbon measures. individual behaviour, meaning that the application of such measures may be confined to a small proportion of total urban GHG emissions. In a context of limited municipal capacity, regulations can be difficult to monitor and enforce.

Enabling • Information and • Education campaigns for Enabling measures can require relatively Enabling measures are dependent on the goodwill awareness-raising walking and cycling little financial or political investment. They and voluntary actions of businesses and

• Incentives • Grants/loans for low-carbon enable municipal governments to benefit communities who may not be forthcoming. technologies for households/ from the resources and capacities of a range Assessing and verifying the impact of GHG businesses of other urban actors in reducing GHG emissions reductions from such measures is often

• Partnerships • Development of voluntary emissions. Through involving a range of impossible and it may be difficult to evaluate their GHG emissions reduction different partners, they may increase the cost effectiveness.schemes for local businesses democratic mandate for acting on

climate change.

Sources: Bulkeley and Kern, 2006; Bulkeley et al, 2009; Hammer, 2009; Martinot et al, 2009; ICLEI, 2010

Table 5.12

Municipal modes ofgoverning climatechange

The self-governingmode remains thedominant approachadopted by municipal authoritiesin response toclimate change


the use of fossil fuels and economic development, and thepolitical and social interests that this sustains.

n Self-governingHistorically, self-governing has been central to municipalefforts to address climate change, particularly in cities indeveloped countries.118 In this mode, there are three princi-pal means through which municipal authorities have soughtto reduce their own GHG emissions (see Table 5.12). Thefirst is through the management of municipal buildings,fleets and services. Local authorities vary considerably interms of the building stock, vehicles and infrastructuresystems that are under their direct control; but in addition tolocal government buildings, this can include schools,community and health centres, libraries and leisure centres;vehicle fleets for waste collection and road maintenance; aswell as energy systems that provide heat and power formunicipal buildings or local authority housing. Actions caninclude technical measures, such as retrofitting buildingswith energy efficiency measures – for example, in Yogyakarta(Indonesia), Johannesburg (South Africa) and Mexico City –and demand-reduction programmes for employees (see Box5.12). In Buenos Aires (Argentina), for example, the localauthority expressed concern that, because employees do notbear the cost of energy, energy-saving measures were notbeing put into place. Thus, employees were given newguidance and training to prevent wasting energy in publicbuildings. In order to encourage behavioural change, theCity of Melbourne (Australia) has implemented a 0.5 percent performance-related pay increase for staff if they meettargets for improving the environmental performance of theorganization.

The second is through procurement policies. Thesecan include purchasing renewable energy for the municipal-ity and, in the transport arena, buying alternative low-carbonfuels.

Third, local authorities may aim to lead by example,establishing best practice principles, or demonstrate the useof particular technologies or social practices to facilitatetheir widespread adoption by other local actors. Projectsimplemented by these means include setting targets forreducing GHG emissions or the use of renewable energy,with a recent survey of 160 cities finding that at least 125had such targets in place,119 as well as demonstrationprojects and promotional campaigns.

Overall, research suggests that within developed anddeveloping countries, the self-governing mode of addressingclimate change is prevalent across different urban policysectors. The ‘reasons for embracing [local government],institutional actions are straightforward: they requireminimal or no community buy in, creating little politicaldebate; they usually produce direct returns with respect tocost savings; they produce quick, verifiable reductions inemissions’.120 The ability to demonstrate leadership onclimate change mitigation and accrue additional (financial)benefits at relatively little economic, political or social costhas led to a strong emphasis on municipalities undertakingself-governing actions. However, while such measures mayprovide the initial step towards establishing climate change

policy, the effectiveness of self-governing measures in reducing urban GHG emissions is limited by the extent ofthe municipal estate and operations. In the majority of cases,municipal GHG emissions constitute a small proportion ofthe total emissions in a city. In this context, too muchemphasis on the self-governing mode may detract attention(and resources) from the broader challenges of reducingGHG emissions across the city.

n ProvisionThe provision mode for governing climate change involvesboth the development of low-carbon infrastructure systemsand the delivery of ‘green’ consumer services by municipalgovernments (see Table 5.12). Historically, municipal author-ities have had a strong role in the development of urbaninfrastructures – energy, water, waste, road and rail net-works – and up until the mid 1990s municipalities contin-ued to own their energy generation, water provision, publictransport and waste services. In the years following WorldWar II, local governments in the UK and North Americabegan to sell off such assets, and with the rising tide of neo-liberalism in the utilities sector, many such companies inother developed countries were sold during the 1980s and1990s. As a result, most municipal governments in devel-oped countries have limited capacity and direct respons-ibilities for delivering low-carbon energy infrastructures,although there are some notable exceptions (see Box 5.13).Rather, these networks are provided by an increasinglydiverse set of partnerships and private actors.121 In develop-ing countries, municipal governments often retain some rolein the direct provision of public services and public transportnetworks alongside new private providers and public–privatepartnerships, creating the potential for governing climatechange mitigation through this mode. However, suchnetworks are limited in their social and spatial coverage, andprovide far from universal access to basic services. Incontexts where meeting basic needs for energy, sanitationand mobility are pressing, the ability for municipal govern-ments in developing countries to take climate changemitigation into account is limited.

Despite these limitations, municipalities have soughtto pursue climate change policy through the provision ofinfrastructures and services. Municipalities have beeninvolved in the creation of low-carbon communities, such as

The provision modefor governing climatechange involves boththe development oflow-carboninfrastructuresystems and thedelivery of ‘green’consumer servicesby municipal governments

Box 5.12 The Green Lighting Programme in Beijing, China

The Green Lighting Programme was initiated in Beijing in 2004. One of its mandates focuses onreplacing normal lights with energy-efficient light bulbs in 2046 primary and middle schools in18 counties and districts. The result was that it replaced 1,508,889 light bulbs, which saved14.4MW of electricity valued at 8.21 million RMB (US$1.05 million), and reduced annual CO2emissions by 14,535 metric tonnes. The project also increased student awareness and knowl-edge of the concept of saving energy. In 2008, the project was extended to installenergy-efficient lighting in 1263 bathrooms inside the 2nd Ring Road, 70 subway stations,114km of subway tunnels, and in government buildings, hotels, commercial buildings and hospital buildings. The Beijing Development and Reform Commission estimates that 39MW ofelectricity can be saved each year through the installation of energy-efficient light bulbs.

Source: Zhao, 2010

the New Town Development Plan in Seoul (Republic ofKorea), which aims to build 277,000 new apartments withdistrict heating, estimated to cost US$2.6 billion.122 In thebuilt environment, municipal governments have been invol-ved in the provision of energy efficiency measures to existingbuildings – for example, Mexico City intends to install30,000 square metres of green roofs per year until 2012 – aswell as providing ‘green’ services to householders, includingenergy audits and retrofitting packages undertaken in citiessuch as Melbourne (Australia) and London (UK). Perhapsmost notable have been measures to provide low-carbonmass transport services. In São Paulo (Brazil), the stategovernment planned to invest more than US$7 billion fromthe Inter-American Development Bank during 2007 to 2010in order to modernize train lines and provide new bus infra-structure – upgrades which it is thought will reduce emis-sions by 700,000 tonnes of GHGs that can then be sold inthe CDM market.123

Seeking to govern climate change through the provi-sion of infrastructure and services has the potential forfar-reaching impacts upon urban GHG emissions by changing

the carbon intensity of energy, water and waste services,reducing the carbon footprint of the built environment,fostering sustainable forms of urban development andproviding low-carbon energy and travel choices for house-holds and businesses. This potential appears to be mostsignificant in cities where municipal governments may retainownership or control of infrastructure networks and wherebasic needs have been met. However, such measures alsohave the potential to be socially progressive, providing theimpetus for upgrading social housing and public transportservices in deprived urban communities in developed anddeveloping countries (see Box 5.14). In seeking to realizethis potential, access to capital investment is likely to be akey barrier, suggesting that donor agencies and developmentbanks may play a central role in making appropriate forms offinance available for the development of low-carbon urbaninfrastructure networks.

n RegulationWhile research suggests that the regulation mode of govern-ing is the least popular approach adopted by municipalgovernments, it can be very effective in terms of reducingGHG emissions. Three different sets of mechanisms aredeployed in this mode. First, and least common, is taxationand user fees, which have predominantly been deployed inthe transport sector – for example, congestion charging (seeBox 5.9) or levies on vehicle pollution.

Second, land-use planning, an area where municipalcompetencies are often strong (at least in developedcountries), has been used across different policy sectors toaddress climate change mitigation. For example, in urbandevelopment and design, land-use planning is used to stipu-late urban densities and to promote mixed land use in orderto reduce the need to travel, and in the built environmentsector to mandate particular standards of energy efficiencyfor new buildings or, as is the case of São Paulo (Brazil) andBarcelona (Spain), to introduce requirements for the compul-sory use of solar energy supply in buildings of a certain size.Land-use planning is also being used to foster the develop-ment of low-carbon infrastructure. In London (UK),developments over a certain size are required to meet 20 per cent of their projected energy needs through onsite low-carbon or renewable energy generation, measuresdesigned to increase the uptake of decentralized energytech-nologies.124

Third, the setting of codes, standards and regulationsare most common in the built environment sector, wherethey are often set by national governments, althoughexamples can also be found at the municipal level, includingthe ban of certain building products in Vienna (Austria) andMelbourne (Australia); a mandatory energy performancerequirement for large office developments in Australia;125

and mandatory requirements for the use of solar hot watersystems for some buildings in Delhi and Bangalore (India).126

In the transport sector, several municipalities in Europe,such as Paris (France) and Athens (Greece), have experi-mented with schemes to ban vehicles coming into citycentre areas on certain days to reduce congestion and pollu-tion. A further set of indirect measures to reduce GHG

While … the regulation mode ofgoverning is theleast popularapproach adopted bymunicipal governments, it canbe very effective interms of reducingGHG emissions


Box 5.13 Provision of energy in Los Angeles, US

The City of Los Angeles is governed by a mayor–council system with 15 city council districts. Itowns and operates its own electric utility, the Los Angeles Department of Water and Power,which is the largest publicly owned municipal utility in the US. The department provides waterand electricity to the entire population of Los Angeles, and is a proprietary department, whichmeans that it does not rely on taxpayer money. The mayor has driven the policy of achieving arenewable energy goal of 20 per cent renewable energy by 2010 and 35 per cent by 2030.

This goal is likely to be facilitated by the phasing-out of contracts with out-of-state coal-fired power plants and the need to expand solar, wind, biomass and geothermal to meetincreasing energy demand and address possible future energy scarcity. The need to address anaging infrastructure problem further facilitates measures to achieve that goal.

However, there are also major obstacles to this goal. These include resistance to coalphase-out from the department’s labour unions and environmental conflict resulting from thefact that the provision from renewable sources would require the building of new transmissionlines, as renewable sources cannot be built in a location with access to existing transmissionlines.

Source: Schroeder, 2010

Box 5.14 Low-energy and passive housing in Ljubljana, Slovenia

In 2003, the Public Housing Fund of Ljubljana started a programme of environmentally sustain-able refurbishment of existing properties to save energy and improve the quality of life ofresidents, most of whom had very low incomes and could barely afford their rent payments.

Work carried out to date includes two successful refurbishments in Steletova (60apartments) and Kvedrova (20 apartments). New developments are being planned. They incor-porate a range of energy-saving technologies, including high heat-recovery ventilation units, useof liquid earth-heat exchangers, solar thermal and solar photovoltaic. Although funding isprovided by the municipality, the local community has been involved from the outset and hascontributed to the municipality’s annual housing action programme. The project appears tohave contributed to the reduction of GHG emissions, as well as improving the relationshipbetween tenants and the Public House Fund. The experience gained in Ljubljana is beingextended to neighbouring countries with similar conditions.

Source: BSHF database (www.worldhabitatawards.org, last accessed 22 October 2010)

emissions includes the implementation of standards forimproving the energy efficiency and emission of pollutantsfrom vehicles in cities such as Lima (Peru), Delhi (India) orBogotá (Colombia).

The regulation mode of governing provides municipalauthorities with a set of tried and tested policy instrumentsthrough which to address climate change. The directed,transparent and enforceable nature of these instrumentsmeans that they can be very effective in achieving reductionsof GHG emissions, especially in terms of targeting the use ofparticular technologies and encouraging behavioural change.However, regulation can be difficult to implement. Thecharacteristics that give it strength – its targeted andenforceable nature – can also attract opposition from thosewho will be adversely affected by the need to comply withand bear the costs of new standards, plans and taxes.Moreover, local governments may lack the institutionalcapacity to enforce regulations, particularly in cities in devel-oping countries with limited resources.

n EnablingMunicipalities have also deployed mechanisms to enableother actors to reduce GHG emissions. Research suggeststhat the enabling mode of governing climate change hasbeen particularly important in developed countries, thoughit may now also be gaining ground amongst municipalgovernments in developing countries.127 Three mainapproaches have been used by municipalities to facilitateaction to reduce GHG emissions within the city. First,various forms of information and education campaigns havebeen implemented. Such initiatives are usually targeted atbehavioural change and are therefore most common in thetwo sectors – built environment and transport – wherechanges in behaviour can have an impact upon GHGemissions. For example, in Hong Kong (China), the munici-pality has established a programme to promote energyefficiency in the home through reducing the demand forcooling by keeping indoor environments at 25.5°C.128 InDurban (South Africa), the municipality has established twoenergy efficiency clubs with local businesses.129 Throughthese clubs, ‘participants were introduced to techniques forenergy management and auditing, monitoring and targeting,carbon footprint calculations, and making power conserva-tion plans. Members who implemented efficiency measuresreported savings of up to R220,000 [South African rand](US$28,000) for the 1st quarter of 2009, and the concept of“clubs” was generally well received by the industries.’130

This example is particularly interesting as measures targetedat reducing GHG emissions from large industries are notusually part of urban municipal climate change policy.131

However, ‘the effect of such [public information] campaignsis contested and difficult to measure since they are oftenpart of policy packages’.132

Second, municipal governments can use incentives ofvarious kinds – including grants, loans and the removal ofsubsidies or barriers to the adoption of new technologies133

– to encourage the uptake of low-carbon technologies or topromote behavioural change. Such initiatives can be found in

the built environment sector, such as grants for the installa-tion of energy efficiency measures by households, in theurban infrastructure sector, where municipal governmentshave provided loans and subsidies for the purchase of renew-able energy technologies, and in the transport arena, wheresubsidies for using public transport are common.

Third, municipal governments have developed variouspartnerships with business and civil society organizations toreduce GHG emissions. For example, in Hong Kong (China),the municipal government established a set of guidelines forreporting on and reducing GHG emissions from buildings in2008, which identified areas for energy efficiency improve-ment and areas for voluntary action. Since ‘its introduction,37 institutions have signed up as Carbon Audit GreenPartners, including private corporations, public hospitals anduniversities’.134

The enabling mode of governing may have significantadvantages in terms of its potential impact upon the GHGemissions across the city and its (relatively) low upfronteconomic and political costs. Seeking to engage a range ofcommunities and businesses in climate change policy canalso increase the transparency and legitimacy of urban gover-nance. However, there are also two critical limitations. First,such initiatives are restricted to those who are willing toparticipate. For example, in the Durban energy efficiencyclubs, ‘not all major players participated fully… Toyota, forexample, pulled out after the initial two meetings’.135

Second, the voluntary nature of such initiatives means thatthey are difficult to monitor and verify, and cannot be‘enforced’, but rather depend on the capacity of municipalgovernments to persuade others to take action:

… the effectiveness of urban planning andgovernance depends not only upon the assumedcommand-and-control power of a master plan,but upon the persuasive power that canmobilize actions of diverse stakeholders andpolicy communities to contribute to collectiveconcerns. The likelihood of such enablingpower to emerge is higher in the societieswhere power is more diffused and is transpar-ently exercised… On the contrary, in thesocieties where power is concentrated, andexercised through corruption and coercion,such consensual processes pose a formidablechallenge.136

A recent assessment of policy instruments for GHG mitiga-tion in the buildings sector concluded that:

Although instruments in [the support, informa-tion and voluntary action instruments] categorymight be considered rather ‘soft’ they can stillachieve significant savings and successfullycomplement other instruments. However, theyare usually less effective than regulatory andcontrol measures.137

The enabling modeof governing climatechange has beenparticularly important in developed countries

The enabling modeof governing mayhave significantadvantages in termsof its potentialimpact upon theGHG emissionsacross the city andits (relatively) lowupfront economicand political costs


The implementationof climate changemeasures by privatecompanies, internationalnetworks and external publicagencies raisesquestions about thelegitimacy of thedecision-makingprocess and how andby whom thebenefits, and costs,are borne

Modes of public–private collaboration inurban climate governance

As discussed above,138 the restructuring of the state hasresulted in the increasing involvement of a number of publicagencies and private actors in urban climate change gover-nance. In parallel to the approaches developed withinmunicipal authorities, this Global Report identifies three‘modes’ of public–private collaboration in urban governance– voluntary, private provision and mobilization – which arebeing developed in order to address climate change (seeTable 5.13). This having been said, it should be noted that, inpractice, there is some degree of overlap between thesethree ‘modes’. Importantly, such initiatives do not only seekto reduce GHG emissions from one organization or group ofpartners, but do so explicitly in the name of one or more city.In this manner, the city has become a key arena within thebroader landscape of climate governance.

The evidence reviewed for this chapter suggests thatpublic–private collaboration in climate change governancecan be found in both developed and developing countries,and across the urban development, built environment, urbaninfrastructure, transport and carbon sequestration policysectors. While limited data on this relatively new phenome-non is available, these approaches appear most likely to beadopted by partnerships or networks than by individualorganizations, and to be concentrated on the adoption ofvoluntary standards for energy and water efficiency, theprovision of low-carbon urban developments and infrastruc-ture networks, and the mobilization of behavioural changesto reduce energy and transport use.

Despite their relatively small scale, the emergence ofthese new forms of urban climate governance may havesignificant implications for achieving GHG emissions reduc-

tions. The involvement of private actors and external publicagencies can provide additional sources of expertise andresource, as well as influence over sources of GHG emissionsthat may otherwise lie outside of the control of municipalauthorities. The participation of a range of organizations andcommunities in addressing climate change can provide ahigh profile for the issue, easing the path for municipalpolicies, and potentially offer a means for enhancing thelegitimacy and representativeness of local action.

However, partnerships should not be treated as apanacea. Coordinated action requires both substantialcommitments from the partners and the ability of the organi-zations to participate effectively (see Box 5.15), and supportmay suddenly be withdrawn when the partnership fails tomeet the objectives of one or some of its members.Partnerships can also be exclusive, serving to promote theinterests of one group of actors at the expense of others.139

This can be especially problematic in developing countries,where empirical evidence suggests that partnerships maylead ‘to city government support for projects, programmes,and partnerships with powerful private-sector interests thathave very large carbon footprints (in their construction andfunctioning) and also do little or nothing to address the keyneeds of low-income urban residents (including addressingthe infrastructure deficit)’.140 Likewise, the implementationof climate change measures by private companies, interna-tional networks and external public agencies raisesquestions about the legitimacy of the decision-makingprocess and how and by whom the benefits, and costs, areborne.141

n VoluntaryVoluntary approaches to addressing climate change includethose which are based on changes to existing practices


Mode of governing Policies and mechanisms Examples Advantages Limitations

Voluntary • Changing practices • Voluntary offsetting schemes Voluntary measures are under the direct Voluntary measures may be limited to those that • Demonstration projects • Building-integrated control of the organizations involved and can provide a financial return within the (short)

photovoltaics can provide quick and cost-effective means time horizons of commercial organizations. • Targets and standards • Voluntary energy of reducing GHG emissions. Adopting Changes in political or economic circumstances

efficiency standards voluntary standards or codes of practice can easily derail such initiatives. Undertaking can provide a testing ground for future voluntary measures can be a ‘stalling’ tactic to legislative requirements. Voluntary measures delay or avoid regulation. Such measures can also are often adopted for reasons of corporate lack transparency and accountability with few if social responsibility and can provide a any penalties for failing to comply. means for holding private-sector actors accountable for their carbon footprint.

Private provision • Urban infrastructure • Investment in waste-to-energy The provision of low-carbon infrastructures The provision of low-carbon infrastructure and systems schemes and services has potential for significant services may be limited by the terms and

• Low-carbon • Energy service companies reductions in GHG emissions by changing conditions attached to investment. In addition, technologies and the carbon intensity of utility provision, the provision of infrastructure and services is services altering the choices available to households only one factor shaping their use and may not

and businesses across the city. lead to an overall reduction in GHG emissions without additional measures.

Mobilization • Information and • Energy efficiency advice Mobilizing other private- and public-sector In order to be effective, mobilization depends on awareness-raising schemes actors to reduce GHG emissions can provide the goodwill and voluntary actions of businesses

• Capacity-building • Mentoring schemes a means of spreading best practice and and communities who may not be forthcoming. • Incentives • Access to subsidized energy scaling up demonstration projects. Partnerships and networks are reliant on

efficiency technologies By engaging a range of partners, organizations continued interest and investment, which may be can limit the costs of acting and reduce any difficult to sustain through changes in personnel, disadvantages of being the ‘first mover’. politics and economic circumstances.By forming partnerships and networks of like-minded organizations, actors can strengthen their political position and claims to legitimacy.

Table 5.13

Public–private modesof governing climatechange

within organizations and communities, demonstrationprojects, and voluntary targets and standards. In the firstcategory, for example, are voluntary commitments to changehow energy and water are used within buildings, experi-ments with the use of alternative fuels, and voluntarycarbon-offsetting schemes. The second category includes,for example, initiatives that seek to demonstrate the poten-tial of energy-efficient buildings, or the economic and socialfeasibility of low-carbon technologies in the urban infrastruc-ture sector. The third category includes schemes which setvoluntary benchmarks for achieving GHG emissions reduc-tions, such as those promoted by ‘carbon reduction actiongroups’ at the community level.142

Community-based climate change initiatives seem toadopt a mixture of these approaches. One such example are‘transition towns’, community-based initiatives found in theUK, North America and Australia that seek to reduce GHGemissions and address the challenge of ‘peak oil’143 byencouraging the development of the local economy, localfood production, reducing demand for energy and transport,and the use of renewable energy.144 For example, theTransition Sydney initiative in Sydney (Australia) providespresentations and films for local groups on how to addressthe challenges of climate change and peak oil, a website forsharing information, and support for community groupsseeking to reduce their use of fossil fuels. In Bristol (UK), theTransition initiative offers home energy auditing training andvarious types of information and support for membersseeking to reduce their individual GHG emissions. Anotherexample is the development in Mumbai (India) since 1996 ofmore than 200 ‘advanced locality management groups’,mainly to organize local waste management programmes,which are now moving into climate change mitigation activi-ties such as the installation of solar water heaters or thedevelopment of awareness campaigns in their neighbour-hoods.145

Such schemes have the potential to offer a progres-sive and inclusive approach to mitigate climate change,tackling issues of social and environmental justice alongsidereducing GHG emissions. However, they are – perhapsnecessarily – small in scale and often politically marginal,suggesting that their wider impact upon climate changemitigation may be limited. Their very basis on voluntaryaction may also be a limitation, with few means to assess thecontributions that are being made or for organizations toaccount for their actions. At the same time, a growingemphasis on voluntary, primarily community-based, res-ponses may serve to shift accountability from actors withresponsibilities for the bulk of (urban) GHG emissions tothose who have little in the way of power to address eitherthe causes or consequences of climate change.

n Public–private provisionWhile municipalities can set the frameworks within whichnew urban development takes place and infrastructuresystems are developed, they may have limited jurisdictionover the provision of housing and the development of energy,water, waste and transport services.146 As a result, partner-ships between public and private actors have become a

common means through which urban development andinfrastructure projects, including those which seek toaddress climate change, are delivered. In addition, theemergence of the CDM and other carbon markets has led toa range of new partnerships involving municipal govern-ments, urban public utility providers, national governmentsand carbon ‘brokers’ in the implementation of low-carboninfrastructure projects, such as energy-from-wasteschemes.147

A second means through which public–private provi-sion is taking place is through the delivery of low-carbontechnologies and services. One example of such an approachhas been the establishment of the London Energy ServiceCompany in 2006, a partnership between the LondonClimate Change Agency and the energy company EDF inorder to develop decentralized energy systems.148 TheClinton Climate Initiative has also sought to develop access to energy service companies amongst its partnercities through developing a ‘unique set of contracting termsand conditions, including streamlined procurement, trans-parency in pricing, and other processes that reduce projectcost, development time, and business risk’.149 While doubtsmay be expressed about the potential applicability of suchprojects to a large number of cities, and of the politics ofaccessing such favourable terms and conditions, it doessuggest that alternative business models and financialarrangements can provide a crucial mechanism for achievingreductions of urban GHG emissions.

Given the challenge of urban governance and theprivatization of urban utility networks, in most cities munici-pal authorities have little choice but to work with otheractors in the provision of urban infrastructures. As discussedabove, partnerships may provide benefits – in terms ofresources, knowledge and the pooling of different strengths– but also have significant limitations. In the case of climatechange mitigation, these limitations may be exacerbated bythe range of actors involved and their diverse interests,ranging from local community groups to international finan-cial organizations and other actors in the carbon market.While it is too early to tell what the impact might be, careneeds to be taken that such responses to climate change donot serve to deepen existing urban inequalities.

n MobilizationA third mode through which public–private urban climatechange governance is taking place can be termed mobiliza-tion, where partnerships and networks seek to facilitate thereduction of GHG emissions through the provision of adviceand information, capacity-building and incentives (see Table5.13). These approaches can be deployed internally, amongstthe members of a partnership or network, or externally,through broader constituencies of business organizations,communities or individuals. Several private organizations,partnerships and networks have sought to mobilize actionthrough providing advice and information. For example, inBeijing (China), Friends of Nature Beijing have led acampaign to maintain indoor temperatures at 26°C and limitthe use of air conditioning in order to reduce GHGemissions. In Manchester (UK), a consortium of public and

Voluntaryapproaches … havethe potential to offera progressive andinclusive approachto mitigate climatechange, tacklingissues of social andenvironmentaljustice alongsidereducing GHGemissions

Partnershipsbetween public andprivate actors havebecome a commonmeans throughwhich urban development andinfrastructureprojects, includingthose which seek toaddress climatechange, are deliv-ered

Given the challengeof urban governanceand the privatizationof urban utilitynetworks, in mostcities municipalauthorities havelittle choice but towork with otheractors in the provision of urbaninfrastructures


private actors has sought to engage individuals in reducingGHG emissions through a ‘pledge’ campaign (Box 5.15).

International networks,150 including C40, ICLEI, theClimate Group151 and the Clinton Climate Initiative, havedeveloped extensive programmes and tools for providingmunicipal authorities and private-sector actors with infor-mation about current and future levels of GHG emissionsand potential strategies to mitigate climate change, includ-ing, for example, reducing energy use, and adopting low-

carbon forms of urban development and alternative modesof transport. In addition to providing advice and informa-tion, these international networks – usually working inpartnership with a range of municipal governments, publicagencies and private-sector actors – have also developedstrategies to build capacity and provide incentives in orderto engage urban actors in climate change mitigation (seeBox 5.16).

These examples suggest that the mobilization modeof governing is becoming an important means through whichurban stakeholders and communities are undertakingclimate change mitigation. However, as illustrated by thecase of Manchester (UK) (see Box 5.15), the effectiveness ofsuch initiatives in reducing GHG emissions may be limited.In parallel to the enabling mode of governance, mobilizationefforts may be hampered by limited participation and itsreliance on powers of persuasion. Furthermore, questionscan be raised about the mandate of private and public–private partnerships to call on others to act upon climatechange, and of the extent to which they can be held toaccount by those who participate in such initiatives. Whilemobilization efforts may enable a cross-section of urbanstakeholders and communities to respond to climate changemitigation, they may equally serve to promote particularvisions of what responding to climate change means at theurban level, failing to account for existing inequalities orchallenging the fundamental causes of the problem.

The mobilizationmode of governingis becoming animportant meansthrough whichurban stakeholdersand communitiesare undertakingclimate changemitigation


Box 5.15 Manchester Is My Planet: Mobilizing the community?

In 2005, Manchester Knowledge Capital, a strategic partnership comprised of universities, local authorities, public agencies and leadingbusinesses in the Greater Manchester region (UK) launched Manchester Is My Planet, a programme of initiatives aimed at engaging localcommunities and individuals in reducing their greenhouse gas (GHG) emissions. Based on pilot studies, and supported by funding (approxi-mately UK£150,000) from the national government, the programme asked people to ‘pledge to play my part in reducing Greater Manchester’scarbon emissions by 20 per cent before 2010 in order to help the UK meet its international commitment on climate change’. The schemequickly gathered around 10,000 pledges, resulting in a visit by then Prime Minister Tony Blair and his Cabinet seeking to endorse an exampleof the successful mobilization of citizens around the climate change agenda. With further funding from the UK’s Climate Change ChallengeFund (approximately UK£55,000), a further 8000 pledges were secured by March 2008. However, with reduced funding, work on theprogramme has been limited to the continued development of its website and the number of pledges currently stands at around 21,000,which according to the programme’s organizers suggests an annual saving of 44,600 tonnes of CO2.

This case illustrates the potential for collaboration between public and private actors to mobilize members of the community to acton climate change issues. However, there are a number of limitations to such schemes. First, the request to pledge to reduce GHG emissionshas not been accompanied by measures to develop the knowledge and capacity of citizens to take action. Second, undertaking the pledge, aswith other voluntary actions, carries no penalties for non-compliance. Third, in the absence of extensive monitoring the impact of such initia-tives upon reducing GHG emissions is difficult to determine. Research conducted by Manchester Is My Planet suggests that over 90 per centof the pledgers took some form of action, while over 70 per cent encouraged others to reduce their energy consumption. However, it is diffi-cult to verify such findings or know whether changes are the result of this particular initiative.

Regardless of the potential impacts upon Manchester’s GHG emissions, research suggests that the Manchester Is My Planet initiativehas been politically important. First, it helped to establish climate change as an issue on local political agendas, signalling to politicians thatmembers of the public were concerned about the issue. Second, it provided an example of ‘best practice’ for the national government and forreplication by other local authorities and partnerships in the UK. This case therefore suggests that efforts of climate change mitigation takingplace ‘outside’ the state and through the mobilization of individuals and communities can have a direct bearing on the future of urban climatechange governance.

Source: Silver, 2010

Box 5.16 Climate change mitigation initiatives developed by international city networks

• The Climate Group city partnerships focus on the role of some of the world’s biggest cities indemonstrating and delivering the public–private partnerships that, according to them, willbuild up the low-carbon economy. The initiative includes the partnerships ForwardChicago in the US, and the Mumbai Energy Alliance in India.

• The C40 Urban Life programme is a partnership between the C40 and Arup, a consultancyfirm, that operates as a co-operative to implement Arup’s Sustainable DevelopmentIntegrated Approach in several cities. The approach will be piloted in Toronto (Canada),and there are plans to extend the programme to five other cities.

• C40 Carbon Financing is a capacity-building programme to assist existing and emergingmegacities to harness the carbon finance opportunities of the Kyoto Protocol.

• The Clinton Foundation Building Retrofit Program focuses on energy efficiency in buildings andhas, so far, completed 250 projects in 20 megacities around the world.

• The Clinton Foundation Transportation Program focuses both on developing urban transporta-tion systems such as bus rapid transits (BRTs) and advancing carbon-neutral transporttechnologies such as hybrid cars.

Source: www.theclimategroup.org; www.c40cities.org; www.clintonfoundation.org, last accessed 18 October 2010

OPPORTUNITIES ANDCONSTRAINTSThis chapter suggests that significant efforts are taking placeto mitigate climate change in urban areas across the world.The level and range of activities being undertaken by citiesdemonstrate that climate change is an issue firmly on urbanpolicy agendas in both developed and developing countries.What is also clear, however, is that in most cities mitigatingclimate change remains a marginal issue, and that despiteambitious policy targets the realities of reducing GHGemissions are often more challenging than anticipated.152

The overall picture is one of policy fragmentation. Islands ofbest practice can be identified; but comprehensiveapproaches to addressing climate change remain the excep-tion rather than the rule,153 and significant gaps betweenthe rhetoric of reducing GHG emissions at the urban leveland the realities of putting such policies and schemes intopractice can be found.154 The critical factor shaping urbanresponses to the challenges of mitigating climate changeseems to be governance capacity.155 In this context, thissection reviews the evidence concerning the opportunitiesand constraints that shape governance capacity according tothree broad categories: factors that are institutional, thosewhich are technical or economic, and those which are politi-cal in character (see Table 5.14).

Institutional factors shaping urbangovernance capacity

Institutional factors which shape urban governance capacityinclude issues of multilevel governance (municipal compe-tencies and the relationships between different institutionsat international, national, regional and local levels); policyimplementation and enforcement; and the presence of alter-native institutional arrangements, such as internationalnetworks and partnerships through which governance capac-ity can be generated. The first two factors are discussed inthe sections below, while the issue of international networksand partnerships is discussed in Chapter 2.

n Multilevel governanceUrban responses to climate change do not take place withina policy or political vacuum. While municipalities are moreor less coherent and have varying degrees of autonomy frominternational policies, and from regional and national govern-ments, the relationship between these arenas of authority iscritical in shaping the capacity to govern climate change. The‘multilevel’ governance of climate change affects urbanresponses to climate change in three key ways: by providingthe context within which urban responses are framed; bydetermining the autonomy and competencies – the dutiesand powers – for municipal authorities to act in response toclimate change; and by enabling policy integration withinand between local authorities.

First, international and national policies have providedthe overall framework for municipal responses. Nationalpolicies have also served as direct drivers for municipalactions. For example, in Sweden approximately ‘half of all

municipalities have adopted climate mitigation goals inaccordance with the national objective of reduced climateimpact as formulated in the Swedish climate strategy’,156

while in China, research suggests that the recent interest inaddressing climate change at the local level has not been inresponse to the issue itself but instead as ‘a response to thecentral government’s expectation for these institutions totake action’.157 However, there are two significant excep-tions to this rule which suggest that an enabling nationalgovernment context is not always necessary for urbanresponses to climate change. In Australia and the US, thenumber of cities developing responses to climate changegrew exponentially during the late 1990s and early 2000s ata time when both national governments withdrew from theinternational process of implementing the Kyoto Protocol.However, in both countries, urban responses were organizedthrough international municipal networks, drew heavily onthe international policy framework, accessed financialresources from federal government funds, and frequentlygained support from cooperative regional-level governmentsto support the development of urban policy. These examplessuggest that an enabling multilevel framework is critical infostering urban capacity even when the political support ofthe national government is absent.

A second critical aspect of multilevel governanceconcerns ‘whether the local authority has broad policy devel-opment and implementation powers, or whether thesepowers are narrowly defined or constrained’158 in relation tocritical policy sectors, such as transport, land-use planning,infrastructure development, building standards and waste.The role of municipalities in these areas is usually defined bycentral or regional governments and is delegated to localauthorities.159 Municipalities that have specific competen-cies for the direct provision of waste, transport or energyservices, such as is the case in many Northern Europeancountries, can have significant capacity to address climatechange that other local authorities lack.160 However, ingeneral, municipalities have limited powers and responsibili-ties with respect to energy policy, pricing and supply, thedevelopment of urban infrastructure (such as transportsystems), the use of economic instruments (such as taxesand charges), as well as energy efficiency standards for build-ings and appliances, and more autonomy with regard toland-use planning, education and voluntary programmes.161

Municipalities can therefore be dependent on the policiesand actions of national governments in order to achieve their


Significant effortsare taking place tomitigate climatechange in urbanareas across theworld … however,… in most citiesmitigating climatechange remains amarginal issue

The critical factorshaping urbanresponses to thechallenges ofmitigating climatechange seems to begovernance capacity

Examples of opportunities Examples of constraints

Institutional • Proactive national/regional government • Limited formal powers for • Membership of international municipal municipal authority

networks • Absence of policy • Formation of partnerships coordination

Technical and • Knowledge of urban GHG emissions • Lack of expertiseeconomic • Availability of external funding • Lack of financial resources

• Flexible internal finance mechanisms • Suitability of technologyPolitical • Political champions • Departure of key personnel

• Recognition of co-benefits • Prioritization of other policy • Political will agendas

• Conflicts with other critical economic and social issues or sectors

Table 5.14

Opportunities andconstraints for governing climatechange mitigation inthe city

policy goals. For example, in London, the Climate ChangeAction Plan recognizes the ‘difficult truth is that in preparingthis action plan we have been unable to present any realisticscenario in which we can achieve the 2025 target …without major national regulatory and policy change’.162

However, actions to reduce GHG emissions may beachieved in cases when municipalities have limited direct orformal powers. First, policy goals can be integrated acrossdifferent levels of government enabling action. A study of theclimate change responses in Helsinki (Finland) shows howenergy consumption in the built environment is determinedby European Union (EU) regulations, such as the EnergyPerformance of Buildings, national regulations, municipalregulatory oversight, and voluntary agreements betweenenergy companies and government departments. In thispolicy area, ‘the different levels of governance are workingwell together … the city is implementing energy perform-ance policies by implementing the building code and grantingenergy aid, and also by participating in the voluntary energyconservation agreement scheme’,163 whereas when it comesto the promotion of renewable energy, policy initiatives at thecity level remain in contradiction with EU and nationalpolicies of increasing renewable energy generation.

A second means through which municipal authoritiescan overcome limited direct competencies for acting uponclimate change is through the development of the limitedopportunities that do exist. In Japan:

… regional and local governments have theauthority to take legislative action when thenational government itself has not enacted anyspecific policies and measures toward climatechange, and the national government does notprohibit them from doing so. Using thisopening, some governors and mayors haveintroduced regional and local ordinances whichmandate businesses and industries to formulateCO2 reduction plans, introduce emissiontrading in the regional and local area, or buyrenewable energy bonds.164

Third, there is considerable evidence that municipalities gobeyond their direct competencies in undertaking actions toaddress climate change. For example, the carbon marketcreated by Rio de Janeiro (Brazil) could have impacts at thenational and international levels while creating partnershipsbetween public, private and civil society actors within andbeyond the city. The capacity challenges which emerge fromlimited autonomy and competencies are only partiallyderived from their relation with national government, butare also dependent on their relation with other partners, andon the ability of local governments to create an ‘enablingenvironment for local civil-society action’.165 Nonetheless,for many municipalities, a lack of formal powers to addressclimate change remains a significant barrier and is onereason for the current focus on ‘self-governing’ acrossmunicipalities.166

The third aspect of multilevel governance that issignificant in shaping municipal capacity concerns issues of

governance fragmentation at the local level and the internaldynamics of municipalities. At the city-region scale, a keyissue concerns the fragmentation of urban governanceacross multiple authorities. For example, a study of climateresponses in Mexico City finds that:

… the administrative structure of city’s gover-nance differs from its boundaries andcarbon-relevant socioeconomic and ecologicalfunctioning. Administratively, the city ismanaged by diverse federal, state and local tiersof government. Yet, the city functions as acomplex system; its core area and localities,activities and households are interlinked byeconomic interchanges and transportationactivities, by fluxes of materials and energy.167

Research has found that in ‘many cities expertise [of climatechange] is still concentrated in the environmental depart-ment’.168 This potentially limits municipal capacity for tworeasons. First, environmental departments are often margin-alized within municipal (and other) authorities and may be inconflict with other parts of the local administration. Second,the ‘cross cutting nature of climate change governancemeans that environment departments or agencies arefrequently not able to implement the policies … that arerequired to address the problem’.169 This challenge ofhorizontal coordination has been exacerbated in manycountries in the wake of neo-liberal reforms, which have ledto the privatization or contracting-out of what were previ-ously municipal services, increasing the number of actorswith whom policy coordination needs to be undertaken. Forexample, in Johannesburg (South Africa), a process of ‘semi-privatization’ has occurred within the local authority that‘creates a silo effect where communication between differ-ent agencies, utilities and the city administration arefragmented’, reducing municipal capacity to address climatechange.170 In this context, ‘mainstreaming, coordination,and cooperation across government agencies is vital’.171 Insome cities, this is being achieved through the developmentof new administrative and institutional structures, such asspecial units or agencies which coordinate climate changepolicies. For example, in London (UK), a Climate ChangeAgency has been established, while in Zurich (Switzerland),an environmental protection unit has been established tosupervise climate policy.172 However, ‘where there is a lackof capacity to do this joining up it is clear that the potentialof local climate change strategies is curtailed’.173

n Policy implementation and enforcementA second set of institutional factors that shapes urban climatechange governance capacity is the ability to implement andenforce policies and measures. In many policy areas, municipalauthorities, particularly but not exclusively those in develop-ing countries, are unable or unwilling to enforce regulationsand standards. For example, in Nigeria increasing energyefficiency in the built environment and appliance sectorssuffers from ‘noncompliance resulting from lack of enforce-ment of the standards … exposing the Nigerian Energy

There is considerableevidence thatmunicipalities gobeyond their directcompetencies inundertaking actionsto address climatechange

the ‘cross cuttingnature of climatechange governancemeans that environ-ment departmentsor agencies arefrequently not ableto implement thepolicies … that arerequired to addressthe problem’

In many policyareas, municipalauthorities, particu-larly … indevelopingcountries, areunable or unwillingto enforce regulations andstandards


Market … and hence the consumers to all kinds of sub-standard technologies (of course energy inefficient) whichmay have even been outlawed in their countries of manufac-ture’.174 In the Ukraine, research has found a similar situationcharacterized by a lack of building standards for energyefficiency coupled with the poor enforcement of those thatexist.175 The effectiveness of energy standards may be particu-larly low in developing countries, given difficulties withenforcement and corruption.176 However, ‘even in developedcountries, the estimated savings from energy codes range from15–16 per cent in the US to 60 per cent in some countries inthe EU’, suggesting that both the levels at which standards areset and the ways in which they are implemented vary signifi-cantly from country to country, in turn affecting the capacityof municipalities to address GHG emissions.177 The avoidanceand corruption of regulations is also a critical challenge. InIndonesia, research found that ‘while zoning permit is theoret-ically supposed to be a tool to control land use, in realitycorrupt practices have rendered it ineffective’.178 However,while at least part of the problem of policy implementationmay be laid at the door of corrupt practices or deliberateavoidance, it also stems from the use of inappropriate policyapproaches and models. For example, in many developingcountries ‘the application of imported models of urbanplanning and government that proved inappropriate to localcontexts and possibilities’ has served to limit the access ofpoor communities to land for housing, in turn provoking theemergence of informal settlements and other slums that donot comply with building and planning regulations.179

Equally, the challenges of implementation are notconfined to municipal authorities. Given the voluntarynature of many of the schemes being developed by theprivate, civil society and donor communities in cities toaddress climate change, issues of compliance, monitoringand verification of achievements also affect urban gover-nance capacity. First, significant challenges exist in terms ofreliably estimating the GHG emissions reductions attributa-ble to specific schemes, a factor which has so far limited theuse of the CDM in urban areas.180 Second, issues of account-ability are also significant. While most schemes rely onself-reporting, there is a growing movement for civil societyactors to be involved in processes of verification, such as thedevelopment of the Gold Standard for CDM and voluntarycarbon markets.181

Technical, material and financial factorsshaping urban governance capacity

A second set of factors that provide opportunities andconstraints for urban responses to climate change mitigationinclude issues of technical expertise, the material infrastruc-tures and cultural practices that determine the possibilitiesfor action, as well as the financial resources available.

n ExpertiseThere are two main ways in which the availability of scien-tific expertise and knowledge has shaped urban governancecapacity for mitigating climate change. First, the growingscientific consensus internationally about the nature of the

climate change problem and the need for urgent action hasbeen a motivating factor for many municipalities. As thescientific community has advocated increasingly stringenttargets for reducing GHG emissions in order to minimize therisk of exceeding a 2°C warming of the atmosphere, citieshave responded with ever more ambitious policy goals.London (UK), for example, has adopted a target of stabilizing‘CO2 emissions in 2025 at 60 per cent below 1990 levels,with steady progress towards this over the next 20 years’.182

In 2002, the City of Melbourne (Australia) adopted a targetof reaching ‘zero net emissions’ by 2020, an approach thathas been adopted by a number of other municipalities in themetropolitan area.183 Equally, the growing scientific consen-sus surrounding the issue of climate change has been asignificant factor influencing the growing importance of theissue on the agendas of private-sector and civil society organ-izations, leading to their mobilization and involvement invarious initiatives.

Second, scientific knowledge has also been significantin the development of local inventories and forecasts of GHGemissions.184 Such inventories are primarily derived from‘scaling down’ regionally and nationally available data, whichprovides a general overview of the likely pattern of GHGemissions and potential areas of future growth. Some municipalities have sought to derive such inventories from‘the bottom up’. One example is Newcastle (Australia),where community-wide GHG emissions derived fromconsumption data, and the equivalent GHG emissions fromelectricity use are updated hourly and reported on the inter-net, on a billboard in the city and in a weekly television newsreport.185 However, most local authorities lack the resourcesto develop such inventories, while those that have sought todevelop a comprehensive picture of GHG emissions acrossthe city have found their efforts constrained by a lack ofdata, much of which is either not collected on a routine basisor regarded as commercially sensitive by energy providers.186

While the lack of data and the expertise or resources togather and assess it is a constraint on the ability of munici-palities to measure progress towards policy targets, it is clearthat – for the majority of cities – a comprehensive picture ofurban GHG emissions may be an impossible goal. It may bebetter to focus efforts on deriving a general overview ofwhere policy attention should be directed.

Beyond the scientific realm, other sources of expert-ise are also important. The example of Durban (South Africa)shows the municipality’s difficulties in participating in inter-national actions such as the CDM because of a lack of stafftraining.187 Once this training is completed, employees maychoose to move on to more profitable private-sector jobs todevelop the same projects. In addition, local authorities mayhave little access to recent developments in architecturaland engineering professions. For example, in Nigeria, ‘lackof information on trends in energy efficient architecture byprofessionals is a formidable obstacle. This has also encour-aged lack of energy conscious building standards andregulations.’188 Skills shortages, however, are not exclusiveto developing countries, although they may be more severeand may affect other aspects of sustainable development notdirectly connected with climate change.

The effectiveness ofenergy standardsmay be particularlylow in developingcountries, givendifficulties withenforcement andcorruption

The example ofDurban (SouthAfrica) shows themunicipality’s difficulties in participating ininternational actionssuch as the CDMbecause of a lack ofstaff training


n Urban systems: Infrastructures and cultural practices

Opportunities and constraints facing the urban governanceof climate change are also structured by the social andtechnical networks that constitute cities – a ‘seamless web’of material infrastructures and everyday practices thatsustain them.189 The first challenge that this raises for thecapacity to mitigate climate change is that of urban morphol-ogy and design. The opportunities for reducing demand fortravel, for example, in a city characterized by urban sprawl orthe rapid development of informal settlements at the periph-ery will be very different from those in a historically compacturban settlement, and urban decision-makers may find theirchoices heavily constrained by existing infrastructurenetworks and spatial form.190 Rather, the comparison oftransport systems between Singapore and New York (US)suggests that a range of factors, including fuel pricing andtourism, will be able to shape urban form alongside urbanplanning.191 Equally, traditional practices of building designcan provide significant barriers to the development andimplementation of mitigation measures. In the Ukraine,research finds that:

… communal services, predominantly heating,are still very inefficient. Outdated systems inpoor condition and high losses due to insuffi-cient maintenance as well as no possibility forheat adjustment are the main reasons for thebad performance ... the efficiency in usingenergy resources in the building stock inUkraine is 4–5 times lower than in westerncountries.192

In Nigeria:

… most buildings seem to be replicas of build-ings in European countries in shape and formdespite marked differences in climatic condi-tions... Window sizes and openings have notresponded to physiological comfort therebynecessitating the use of mechanical devices forincreased air movement. The choice ofwindows tends to be in response more tooaesthetic needs rather than physiologicalneeds.193

Such traditional practices, whether as a result of particularpolitical regimes or the importation of so-called ‘modern’design, can have a detrimental effect on the capacity of citiesto respond to climate change.

A second challenge arises from the nature of the infra-structure systems that supply services, such as energy, waterand waste collection, as well as existing building stock. Forexample, in Helsinki (Finland), the EU target of increasingrenewable energy to 20 per cent of energy supply by 2020 isseen as limited by the current district heating network inwhich biofuels are regarded as the only potential, but stillcostly and potentially ineffective, option.194 The introduc-tion of new vehicle fuels, such as in London’s (UK) ambitious

plans to create a ‘hydrogen economy’, are limited by thenetwork of refuelling stations which may encounter localopposition during the planning and development process.195

In Iran, the programme to substitute fuels by compressednatural gas has been clearly limited by the existence offuelling stations; while 180 filling stations are planned, thepilot programme in Tehran will include only 2.196

n Financial resourcesFinancial resources are both a driver and a barrier to foster-ing urban responses to climate change. Municipal author-ities lacking the finances to provide even basic services fortheir constituents are unlikely to invest in climate changemitigation, given the many competing issues on urbanagendas. A lack of basic service provision in cities in develop-ing countries, and especially for those living in informalsettlements, can reflect ‘local governments lacking theresources to meet their responsibilities – and often withvery limited capacities to invest (as almost all local revenuesgo to recurrent expenditures or debt repayment)’.197

A lack of finances to invest in basic service provisionand in the development of urban infrastructures means thatissues of climate change mitigation are far from a priority,and even where there is commitment to act, financialconstraints may prevent the implementation and enforce-ment of policy goals. For example, in Tuzla (Bosnia andHerzegovina), the municipality had to drop proposals to taxthe air pollution emissions of the local coal-fired power plantbecause of the lack of initial resources to administer theprogramme and the lack of support at the national level.198

While this is an acute challenge for cities in developingcountries, a lack of adequate finance can also act as a barrierto action on climate change mitigation in cities in developedcountries. For example, in the UK, local authorities arebound by strict central government controls over theirfinances, and their ability to provide capital for infrastruc-ture projects and service provision is limited. At the sametime, increasing pressure on local government finances hasmeant that limited funding is available for even small-scaleprojects.199 Often, finding a source of finance is not the onlyproblem: allocating the resources in an efficient way is alsochallenging (see Box 5.17).

Equally, rather than a lack of financial resources,action can be impeded by the financial reporting and distri-bution mechanisms in place in an organization. For example,in São Paulo (Brazil), research has found that issues of finan-cial resources, surprisingly, are not a key factor shaping theearly stages of the development of climate policy and that‘institutional difficulties in reinvesting resources, rather thanactual lack of resources, were reported as the main obsta-cle’.200 A significant factor shaping the capacity of municip-alities and other organizations to respond to climate changeat the urban level is therefore the ability to establish novelmechanisms for distributing funding internally to facilitateinvestment in particular policy measures. This is one area inwhich political champions or policy entrepreneurs (exploredin the section below) have been particularly important inovercoming the ‘inflexible budgetary structures’201 forwhich municipal authorities are usually renowned.

The opportunitiesfor reducing demandfor travel … in a citycharacterized byurban sprawl or therapid developmentof informal settle-ments at theperiphery will bevery different fromthose in a historically compacturban settlement

A lack of finances toinvest in basicservice provisionand in the development ofurbaninfrastructuresmeans that issues ofclimate changemitigation are farfrom a priority

A significant factorshaping the capacityof municipalities …to respond toclimate change … is … the ability toestablish novelmechanisms fordistributing fundinginternally to facili-tate investment inparticular policymeasures


Mechanisms that have been established to leverage internalsources of funding include revolving energy funds (wherefinancial savings from energy efficiency are reinvested inenergy conservation or other climate change projects),energy performance contracting and the establishment ofenergy service companies (where external organizations orcompanies established by municipalities invest in energyefficiency measures and profit from the financial savingsmade).202 In Japan, several local governments are operatinglocal energy service companies that are achieving energysavings of more than 10 per cent.203

Access to external sources of funding is also a keyfactor shaping local capacity to address climate change. Suchsources of funding may come from the EU, national govern-ments, through partnership arrangements, or donororganizations. International municipal networks, such asICLEI’s CCP campaign and the C40, have been critical inleveraging funding for municipalities. One recent initiativein which the C40 is involved is the Carbon Finance CapacityBuilding Programme204 that ‘encourages the use of CarbonFinance to reduce GHG emissions in cities, in particularemerging mega cities’ in developing countries.205 National

governments are also an important source of direct fundingfor municipal responses to climate change. In The Nether-lands, the Klimaatcovenant is a multilevel arrangementwithin which cities are required to complete a performanceassessment of their targets, policies and measures and aregiven funding according to their achievements and popula-tion or area for the implementation of climate plans.206 Inthe US, many climate change mitigation measures have beenassociated with philanthropic activities. For example, thedevelopment of the Plaza Apartments in San Francisco by thePublic Initiatives Development Corporation was supportedby grants from a private utility, Pacific Gas, and a partnershipbetween 31 financial and energy multinationals.

One comparatively new source of funding, and onethat to date has had little impact upon the development ofurban mitigation efforts, is that of carbon finance. As notedin Chapter 2, there are two principal sources of carbonfinance: the CDM, and that from emissions trading.207 InSão Paulo (Brazil), the use of the ‘methane from theBandeirantes landfill (one of the largest in the country) forproducing electricity’ was financed by the CDM, and it hasbeen estimated that this action alone has reduced the city’s

Access to externalsources of funding is… a key factorshaping local capacity to addressclimate change

One … new sourceof funding … is thatof carbon finance...:the CDM, and …emissions trading


Box 5.17 Distribution of resources for climate change mitigation in Mexico City

In 2008 the City of Mexico presented the ClimateChange Action Programme, which introduced a numberof measures in the fields of energy, transport, water,waste, climate change adaptation and environmentaleducation. Some 60 per cent of the total budget (ofsome 61 billion pesos) was invested in transportmeasures and an additional 36 per cent in infrastruc-ture. Only 4 per cent of the budget was invested inmeasures for the built environment. However, while themeasures in the transport and urban infrastructuresectors were expected to reduce carbon emissions by2.1 million tonnes of CO2eq (47 per cent of projectedemission reductions) and 1.9 million tonnes of CO2eq(42 per cent), respectively, built environment measureswere projected to reduce the city’s carbon emission by0.5 million tonnes of CO2eq (10 per cent), suggestingthat the built environment measures are the most effec-tive in reducing carbon emissions.

The analysis in the figure brings a new dimension into the discussion – namely, the disparity ofefficiency of different measures in terms of reducingCO2eq per million of pesos invested. Issues such as the‘rebound effect’ that may cancel the energy efficiencygains of built environment programmes (e.g. ‘efficientlighting in homes’) need to be taken into consideration.Furthermore, the costs and reduction potential of eachmeasure will be different in each city. Overall, theMexico City approach, which targets a wide range ofmeasures in different sectors, is likely to bring the bestresults.

Source: Ciudad de Mexico, 2008; see also Johnson et al, 2009

Built environment

Transport

Urban infrastructure

Effici

ent l

ightin

g in h

omes

CO

2 em

issi

ons

redu

ctio

ns p

er m

illio

n of

pes

os in

vest

ed

3000

2500

2000

1500

1000

500

0

2865

62

1261

6173

400

853

76

533

6688

956

14

208

1035

1407

Ener

gy-ef

ficien

t pub

lic bu

ilding

s

Susta

inable

certi

ficati

on fo

r buil

dings

Ener

gy-sa

ving a

pplia

nces

in pr

ivate

homes

Home W

ater S

aving

Prog

ramme

Metro

exten

sion,

12 lin

e

Tram

corri

dor H

istor

ical C

entre

-Bue

navis

ta

Mass tr

ansp

ort f

leet r

enew

al

Mass tr

ansp

ort c

orrid

or-m

etrob

us

Taxi

fleet

rene

wal

Collec

tive t

rans

port

incre

ase ca

pacit

y flee

t

Non-m

otor

ized m

obilit

y cor

ridor

s

Wate

r dist

ribut

ion in

frastr

uctu

re up

grad

e

Reduc

tion o

f emiss

ions f

rom th

e biol

ogica

l tre

atmen

t of s

ludge

Adjust

supp

ly to

low-d

eman

d per

iods

Bioga

s cap

ture

in B

ordo

Pnien

te IV

stag

e

emissions by 11 per cent. The resulting carbon credits weresold, raising significant finances for investments in ‘socialprojects in the area of the landfill’.208 Similar projects arebeing implemented in Mexico City, Quito (Ecuador), Lima(Peru) and Johannesburg (South Africa). As this examplesuggests, CDM projects may also have significant socialbenefits when they are targeted at low-income sectors of thepopulation, such as is the case in the Kuyasa developmentproject in Cape Town (South Africa),209 although there issignificant controversy over whether the ‘developmentdividend’ of the CDM will be realized in this project, or ingeneral.210 As noted in Chapter 2, as of December 2009,only a small percentage of the CDM projects that had beenregistered worldwide were located in urban areas, and morethan 90 per cent of these were in the solid waste sector.211

The main problem for city authorities in terms of making useof international funding mechanisms such as the CDM isrelated to the lack of an effective city-wide approach tocarbon financing. In Amman (Jordan), the Amman GreenGrowth Programme represents an innovation in this field asthe first city-wide CDM programme worldwide, focusing onwaste, energy, urban transport and urban forestry sectors.212

The lack of urban CDM projects reflects both thecomplexity of the processes involved in the design and verifi-cation of projects, the lack of available and consistent data,the problems of ascertaining ‘additionality’ where a numberof factors may shape GHG emissions reductions, and thefinances involved, with evidence suggesting that projectsthat seek to reduce demand for energy generate lower ratesof financial return than large-scale energy supply or indus-trial projects.213 For example, ‘a transport study of Santiago,Chile … found that costs associated with a bikeway systemand improved bus technology for 462 buses achieved verylimited benefits as a CDM project’.214 The following havebeen identified as the main barriers to expanding the use ofthe CDM in urban areas:

• Small individual projects: typical projects in cities(except for waste management projects in large cities)are small and yield small volumes of emissionreductions.

• Repeated clearances from the same local authority fordifferent projects: for each project activity, developersneed to seek approval, which can be time consumingand cumbersome.

• Lack of good ‘bundling’ agents: due to different budgetprocesses and approval timelines, bundling projectsacross several cities is a complicated process, which isexacerbated by the fact that very few public agencieshave the mandate or capacity to bring together differentcity governments and mobilize project activities.

• Lack of strategic planning by the city: piecemeal assess-ment of projects, proposed by developers, preventslocal authorities from taking a holistic view of theirdevelopment plans and opportunities to reduce GHGemissions.

• Lack of opportunity to structurally build the capacity oflocal authorities to identify GHG mitigation opportunitiesand to monitor emission reductions: the lack of strategic

thinking results in continuation of business as usual,generally in the form of breakdown orientation (i.e.replacement only when equipment is broken beyondrepair), minimum maintenance (only when reportedbroken) and least cost-based purchase of equipment(due to budget restraints).215

Political factors shaping urban governance capacity

Political factors that shape the opportunities and constraintsof urban climate governance can be considered in terms ofissues of leadership, questions of opportunity, the framing ofthe costs and benefits of acting upon climate change, andunderlying structures and processes of political economy.

n LeadershipThe opportunities afforded by two different forms of leader-ship – at individual and organizational levels – have also beencritical in shaping governance capacity to address climatechange in cities (see Box 5.18). Several studies have demon-strated that individual political champions or policyentrepreneurs have been critical to the development andpursuit of policies and projects at the urban level.216 Oneexample can be found in London (UK) where former MayorKen Livingstone was a key figure in the development ofambitious policy targets and the formation of the C40.Operating both within and outside of the public eye, suchindividuals are critical in getting climate change on theagenda of municipal and private-sector organizations, coun-tering opposition, forging coalitions, developing policies, andadvocating particular goals and measures. Evidence suggeststhat the initiation and uptake of climate change mitigationon urban agendas is usually dependent on the presence ofone or more political champion or policy entrepreneur. A keyfactor reducing urban governance capacity for addressingclimate change may therefore be the lack of committedindividuals. However, such individuals are not sufficient forsustaining policy action because of the barriers that they mayencounter and the often temporary nature of their rolewithin any one organization.217 For example, in Durban(South Africa), Mexico City and São Paulo (Brazil), researchhas found that the effectiveness of individuals and of thecoalitions that they form is constrained by the institutionaland federal government contexts within which theyoperate.218

At the organizational level, leadership is also animportant factor in shaping urban governance capacity.Opportunities to be at the forefront of initiatives amongst apeer group – for example, to be the first municipality todeploy a technology, adopt a certain target or achieve aparticular measure – have provided the impetus for action inthe urban arena. Such initiatives play on the growing impor-tance of climate change as a means of fostering organiz-ational reputation, both within municipalities and across thecorporate sector. International networks seeking to fosterurban responses to climate change have, in turn, providedvarious means for recognizing and rewarding such leader-ship, such as the Climate Alliance Climate Star award and

The main problemfor city authoritiesin terms of makinguse of internationalfunding mechanisms… is … the lack ofan effective city-wide approach tocarbon financing

The initiation anduptake of climatechange mitigationon urban agendas isusually dependenton the presence ofone or more politicalchampion or policyentrepreneur

At the organizationallevel, leadership is… an importantfactor in shapingurban governancecapacity


CCP Australia’s Outstanding Council Initiative award, in turnpromoting such forms of leadership. At the same time, beingpart of a ‘leadership group’ has also fostered capacityamongst both public- and private-sector actors to addressclimate change. The C40 is a case in point with its emphasison being a ‘climate leadership group’.219

Within cities, public–private partnerships or voluntaryagreements amongst private-sector organizations also rely onnotions of leadership and innovation. One such example isthe recently launched Forward Chicago initiative, orches-trated by the Climate Group and the mayor of Chicago andintended ‘to engage Chicago’s leading businesses in public–private partnerships to implement selected climate initia-tives’.220 However, this emphasis on the importance ofleadership can also constrain municipal capacity to respondto climate change in several important ways. First, it isclearly impossible for every municipality or private-sectoractor to ‘be the first’ to address climate change and thedanger arises that an emphasis on innovation will mean thatmitigating climate change fails to be adopted as part ofmainstream urban policy. Second, leadership groups are, bytheir very nature, exclusive, with the result that a two-tierapproach to addressing climate change in urban areas couldbe fostered in which the ‘best’ cities attract resources andpolitical support, leaving ‘the rest’, where the majority ofGHG emissions lie, behind.

n Windows of opportunityThe presence of committed individuals and an institutionalframework within which acting on climate change issupported provides a basis upon which windows of opportu-nity can be used to further climate change policy ambitions.Such opportunities can take the form of specific climatechange initiatives, triggering events that create the politicaland physical space for interventions in the city, or sources offunding or political support that can be diverted for climatechange ends.

In terms of climate change initiatives, the participa-tion in international and municipal networks frequentlyprovides windows of opportunity for member municipalities.For Seoul (Republic of Korea), membership of the C40 andthe hosting of the 2009 summit of that network provided abasis for galvanizing action in the city. The invitation to LuisCastañeda Lossio, mayor of Lima (Peru), to make a plenarypresentation about the climate change initiatives in the cityin the 2009 summit propelled the adoption of climatechange mitigation measures, including the use of natural gasin city buses and the municipal fleet and the establishmentof individual grants for exchanging old cars for gas-fuelledones.

Research suggests that major urban events, such assports competitions, can be significant triggers for actions toaddress climate change, providing both the political profileto what might otherwise be routine infrastructure projects,as well as the finances and motivations to undertake whole-sale infrastructure replacement programmes. For example,before the 2010 FIFA World Cup, Cape Town (as well asother major cities in South Africa) was seeking to developBRT systems221 with the aim of achieving a 10 per cent

increase in rail transport use and a 10 per cent decrease inprivate vehicles commuting into city centre between 2005and 2010. The 2008 Olympic Games in Beijing (China), the2006 Winter Olympic Games in Turin (Italy) and the 2006FIFA World Cup in Germany have all been recognized asevents triggering significant environmental action (see Box5.19).

A further means through which windows of opportu-nity are exploited to address climate change occurs wherethere is a degree of commitment to action on the issue, and

Major urban events,such as sportscompetitions, can besignificant triggersfor actions toaddress climatechange


Box 5.18 Political leadership models in Los Angeles, US

The impact of leadership upon climate change action is the central feature of Los Angeles’sclimate change policy. This is evident in three ways. First, the political leadership of MayorAntonio Villaraigosa and his staff has addressed climate change comprehensively and has placedit on the political agenda of the city. This high-level political support has led to the developmentof a climate change strategy and ambitious targets for emissions reductions for Los Angeles,bringing widespread recognition of climate change as a policy issue for the city. Motivation todo so was based on multiple drivers, including personal ambitions, and embedded in the contextof the State of California, which has adopted progressive policies on climate change, such as theGlobal Warming Solutions Act (AB 32).

Second, Los Angeles has drawn on business and civil society leadership in the area ofclimate change to further support its strategies and plans. Segments of the business communityhave shown some leadership in terms of promoting sustainable business conferences and greenbusiness solutions. The local environmental community responded to the mayor’s initial indica-tions of prioritizing the environment by forming a coalition and offering their expertise in theprocess of drawing up an action plan.

Third, national and international leadership has been a key element in the Los Angelesstrategy. Action is also motivated by the aspiration to become the largest green city in the US.Given the city’s multicultural make-up, it sees itself as a potential model for cities around theworld. Importantly, Los Angeles is collaborating internationally as part of the C40.

Source: Schroeder, 2010

Box 5.19 Trigger events in Beijing, China

The 2008 Olympic Games was a turning point for Beijing’s environmental and climate policy.The city is now generally considered to be a leader, within China, in efforts to improve energyefficiency and develop cleaner urban sources of energy. The 2008 Olympic Games put pressureon the city to improve air quality and tackle other environmental problems. Beijing made greatefforts to achieve a ‘Green Olympics’. For example, it diversified the city’s energy mix away fromcoal to cleaner natural gas and renewable energy. This resulted in many of the Olympic venuesincluding solar panels and geothermal hot water systems, and investments were made in cleanerpublic infrastructure, such as a fleet of alternative fuel buses and taxis. Beijing also developed itsclean energy resources in the form of geothermal heating and wind energy. A total of 174 newgeothermal wells were constructed between 1999 and 2006, reducing CO2 emissions by850,000 tonnes between 2001 and 2006, and the Guanting wind farm on the southern bank ofthe Guanting Reservoir (Beijing’s first wind power station) has the capacity to generate 100million kWh of electricity per year.

Efforts associated with the 2008 Olympic Games increased awareness of climate changeissues among both Chinese government officials and the public. Investments of US$12.2 billionto promote sustainable development had a huge impact upon reducing greenhouse gas (GHG)emissions, as city-wide activities such as energy saving, fuel switching and carbon sequestration(through tree-planting) according to some estimates generated 80 million tonnes of CO2reductions during the period of 2001 to 2006.

Source: Zhao, 2010

sources of additional funding can be diverted to supportpolicies and measures. For example, in São Paulo (Brazil), the ‘need [for] controlling air pollution was a window ofopportunity for implementation of climate change relatedpolicies’.222 Similarly, in Rio de Janeiro (Brazil), the federalgovernment’s commitment to build 1 million low-costenergy-saving houses in disadvantaged neighbourhoods by2010 provided the opportunity to experiment with andimplement energy-efficient construction materials.223

n Issue framing and the realization of co-benefits

The bundling of climate change mitigation with other poten-tial social or environmental benefits at the city level may be apotential trigger of climate change action and a factor thatmay determine the long-term success of the initiatives. Theissues that may influence climate change mitigation actionsare varied and depend largely on local conditions.224

The examples discussed in this chapter show that awide range of potential co-benefits may be associated withclimate change mitigation. Overall, initiatives in the builtenvironment are often associated with energy savings orwith issues of social justice, particularly when actions areassociated with developments or improvements targetinglow-income population sectors. Energy efficiency program-mes are often linked with financial savings. This may beparticularly significant for municipalities as ‘local govern-ments have come to realize the link between energy savingand climate change. They can claim credit for action on bothissues even though they only take action related to energysaving; they are in essence killing two birds with onestone.’225 Actions related to urban infrastructure may bringdirect benefits in terms of improvement in access, affordabil-ity and service. In Lagos (Nigeria), climate change mitigationinitiatives in the waste sector are linked to improvements inthe service and reduction of pollution from waste burning.Actions in the transport sector are associated with reducingcongestion and reducing air pollution, through, for example,BRT and congestion charges. Finally, carbon sequestrationprogrammes, particularly those linked with urban tree-plant-ing, are often associated with ideas of city beautification,such as the Greening Soweto proposal in Johannesburg. Thecombination of social justice and sustainable developmentconcerns may open windows of opportunity for the advance-ment of climate change mitigation actions.

Such strategies may be particularly important incontexts of ambiguous or overtly hostile responses toaddressing climate change in cities. However, joining climatechange mitigation initiatives with other co-benefits may alsohave downsides. For example, linking climate change withthe local sustainability agenda may mean that climate changeactions need to be limited to those about which consensuscan be reached, while issues that require a stronger commit-ment may be dropped. For example, energy efficiencymeasures can generate consensus between governmentauthorities, industry and civil society about their environ-mental and economic benefits. On the other hand, measuresto control and limit the demand for energy and transportmay be discouraged. Similarly, despite its achievements in

creating a right of way for pedestrians, the Pedestrian RightsCharter in Porto Alegre (Brazil) was approved only when anumber of considerations that restricted individual motor-ized transport in the city were dropped. Furthermore, thebenefits of such initiatives are unlikely to be equally shared,and ‘There are many examples of environmental projects incities that have served only the narrow interests of wealthiergroups, or that have included an active anti-poor politicalagenda.’226 In this manner, advocating the need to addressclimate change may further entrench existing inequalitieswithin cities.

n Urban political economies: Conflicting agendas

At the most fundamental level, struggles have emerged overwhether cities should or should not be addressing climatechange. In many cities, the arguments ‘not on my turf’ and‘not in my term’ are prevalent, particularly in developingcountries where resources are limited and other concernsare more pressing.227 In these cases, ‘subnational govern-ments may be overloaded with other local demands, andclimate policy may be down on the list of priorities’.228

In more affluent urban contexts, efforts to mitigateclimate change are often in direct conflict with dominanturban political economies. The very factors that are regardedas driving urban growth – including the availability of cheapland at the urban fringe, short payback periods on capitalinvestment, increased personal mobility, and the growingconsumption of energy- and resource-intensive goods andservices – are also those which contribute to rising GHGemissions.229 In this context, initiatives which seek to changepatterns of production or to reduce levels of consumption mayencounter significant opposition. These issues may be particu-larly pressing for cities in developing countries, where ‘GHGmitigation has a negative connotation because of the percep-tion that this will deny them of their basic right to growth inhuman services and economic activities; the prospects of“reduced growth” or “no growth” are not feasible’.230

Climate change mitigation can contribute to createconditions that favour sustainable development, as discussedabove. However, this is not a given, particularly in thosecases in which climate change mitigation (and other environ-mental concerns) have been used by urban elites to attackthe interests of the urban poor.231 In particular, researchershave identified two areas in which mitigation may haveserious social consequences for urban populations in devel-oping countries: when it detracts attention from adapt-ation232 and when mitigation measures have impacts inparticularly disadvantaged sections of the urban popula-tion.233 For example, street-lighting programmes whichpromote the substitution of standard bulbs by lightinginnovations such as light-emitting diodes (LEDs) – such asthe one promoted by the Climate Group in Mumbai(India)234 – may direct investments to affluent areas wherelighting infrastructure is already in place, while detractinginvestments from developing lighting infrastructure in thewide slum areas of the city.

Such tensions between dominant forms of urbangrowth and climate change mitigation are, however, also

The bundling ofclimate changemitigation withother potentialsocial orenvironmentalbenefits at the citylevel may be apotential trigger ofclimate changeaction and … maydetermine the long-term success of theinitiatives

Energy efficiencyprogrammes areoften linked withfinancial savings

Carbon sequestra-tion programmes …are often associatedwith … city beautification

In more affluenturban contexts,efforts to mitigateclimate change areoften in directconflict withdominant urbanpolitical economies


discernible in cities in developed countries. In the US, forexample, climate change mitigation is likely to be prioritizedin those communities which are most likely to be affected bythe impacts of climate change, and those with a ‘liberal’political constituency.235 In the UK, climate change initia-tives in the transport sector have been undermined by thepriority given to economic considerations and the stress onthe need to increase the demand for travel.236 The long-termexperience with transport regulation and urban economy inÅrhus (Denmark), however, suggests that the focus onindividual motorized transport is not always the best or theonly strategy to improve the local economy.237 That suchalternatives are often overlooked may be due to the ways inwhich the scope for municipal action on climate change ispredetermined by neo-liberal political and economic condi-tions. For example, research in Portland, Oregon (US), foundthat climate actions were confined to:

… elements of energy consumption that couldbe influenced in an acceptable way by themunicipal government. Energy used in flights toand from Portland International Airport, forinstance, was excluded. Also excluded were thesignificant amounts of energy used in importingand exporting commodities, and the energyactually embodied in commodities.238

COMPARATIVE ANALYSISAs demonstrated above, cities across the world are undertak-ing a range of measures to address climate changemitigation. From a handful of pioneering cities during the1990s, the number of urban municipalities participating inclimate change mitigation efforts has expanded significantlyover the past two decades. Alongside a growing number ofcities in developed countries, the analysis presented in thischapter suggests that climate change mitigation is becomingan increasingly important issue for cities in developingcountries as well. Most urban mitigation efforts have beenimplemented after the adoption of the Kyoto Protocol, withmany initiatives, especially in developing countries, datingfrom the mid 2000s. This reflects the changing internationaland national climate change policy context in which develop-ing countries with growing contributions to global emissions– including China, India, Brazil, Mexico and South Africa –are becoming involved in mitigation efforts. It is also sympto-matic of what has been described as an era of ‘governanceexperimentation’ emerging as a result of the fragmentationof authority for governing climate change between publicand private actors, and a growing dissatisfaction with theoutcomes of national policy processes and internationalnegotiations.239 Despite the growing profile of climatechange as an urban issue, data on the strategies andmeasures being adopted in cities across the world arelimited, especially for cities in developing countries. Equally,where the development of policy and the implementation ofmeasures have been documented, evidence concerning theimpacts and effectiveness of climate change mitigationmeasures is scarce. In this context, detailed comparative

analysis of urban climate change mitigation efforts is notpossible, though some key trends can be observed.

First, the analysis in this chapter suggests that climatechange remains a marginal issue for most of the world’scities. Relatively few cities, especially in developing coun-tries, are explicitly seeking to address climate change mitig-ation, and where this is the case, policy-making is largelyconfined to the environmental domains of municipal govern-ments and, furthermore, the issue of climate changemitigation is one of concern primarily for urban elites.Although there are growing expectations in developedcountries for action on climate change by municipal govern-ments and other urban actors (e.g. in the UK, localauthorities are required to prepare climate change mitigation(and adaptation) plans; and in the US, the Mayors ClimateProtection Agreement has attracted a significant following),there is limited evidence that this is being approached in astrategic or comprehensive manner.240 In regions whererapid industrialization and urbanization is taking place (e.g.cities in Latin America and Asia), there is a growing interestin climate change mitigation. This is, for instance, the casefor cities such as São Paulo, Porto Alegre and Rio de Janeiroin Brazil; Mexico City; Beijing and Shanghai in China; andJakarta in Indonesia, where climate change initiatives haveproliferated during the last four to five years, not only in apiecemeal fashion, but also in the form of articulated andcoordinated climate change action plans. It should also benoted that some developing countries, such as the Philip-pines,241 have adopted national frameworks within whichmunicipalities should address climate change mitigation.However, with limited data available, the extent to whichsuch initiatives are taking place in other cities in developingcountries is not clear.

Furthermore, the analysis presented in this chaptersuggests that governing climate change mitigation is prima-rily being undertaken by municipal governments, althoughforms of partnerships and the involvement of private actorsis increasingly becoming important. There are relatively fewexamples of inclusive and participatory approaches to urbanclimate change mitigation governance. In particular, issues ofgender have received minimal attention.242 Seeking tobroaden the basis upon which climate policy is formulatedand implemented is a critical challenge for cities. Women’sparticipation in climate change decision-making at the locallevel may play a specific role in supporting sustainablelifestyles, developing alternative forms of engagement withthe environment and challenging traditional patriarchalmodels of urbanization and planning.

A second set of trends indicated by the analysis in thischapter concerns regional differences in terms of what citiesare doing and how they are doing it. For example, urbanresponses to climate change are more common in developedthan in developing countries. While international commit-ments and national policy frameworks have providedimportant drivers for these cities, the cases of the US andAustralia – where significant action has been taken at theurban level despite the withdrawal of both countries fromthe Kyoto Protocol – highlight the ways in which municipalgovernments have also pioneered climate policy.243

Climate changeremains a marginalissue for most of theworld’s cities

In regions where rapid industrialization and urbanization is taking place …there is a growinginterest in climatechange mitigation

Some developingcountries … haveadopted nationalframeworks withinwhich municipalitiesshould addressclimate changemitigation

There are relativelyfew examples ofinclusive and participatoryapproaches to urban climatechange mitigationgovernance


Nonetheless, the development of international and nationalpolicy commitments to address climate change in somedeveloping countries – notably, China, India, Brazil, Mexicoand South Africa – is also driving a growing policy interest inthe issue at the urban level. The development and spread ofinternational, national and regional municipal networks hasalso provided a key driver for municipal responses in devel-oped countries, and the expansion of these networks toinclude cities in developing countries is one importantreason for their growing participation in climate changemitigation. In developing countries, mitigation initiativeshave also often been linked with adaptation responses,taking advantage of the potential synergies between both.244

The differences between developing and developedcountries, however, are more apparent when examining themeasures and mechanisms which have been developed toaddress climate change mitigation. In developed countries,emphasis has been placed on the energy sector throughurban design and development, the built environment andurban infrastructure systems. In developing countries, citieshave focused on a more diverse range of urban infrastruc-ture projects, including waste and water systems, as well asissues of carbon sequestration. Those schemes which havebeen undertaken in the urban development and designsector in cities in developing countries have tended to focuson flagship projects, which are often socially and economi-cally exclusive, in contrast to the involvement of civilsociety groups and an emphasis on smaller-scale brownfieldregeneration projects in developed countries. This mayreflect the urban morphologies of these different cities –brownfield sites are likely to be uncommon, particularly inthe rapidly industrializing cities in developing countries – aswell as the availability of resources for creating ‘sustainable’housing.

While projects in the built environment in developedcountries have tended to focus on municipal and residentialbuildings, in developing countries attention has been givento commercial buildings. This reflects the fact that in devel-oped countries, the major challenges in the builtenvironment are related to retrofitting the housing stock, asnew developments are gradually incorporating more efficientdesigns and materials, whereas the contribution of residen-tial dwellings to GHG emissions in developing cities is likelyto be minimal for the vast majority of the housing stock.Furthermore, the focus on commercial buildings reflects thegrowing involvement of private-sector actors in addressingclimate change mitigation in developing countries. Theevidence presented in this chapter also suggests that initia-tives in developed countries are often achieved throughprocesses of self-governing and enabling, while in developingcountries, modes of provision, both public and private, havebeen more significant. Despite these differences, there arerelatively few examples of the development and use of alter-native energy technologies or of explicit policies to tackleclimate change in the transport sector in both developed anddeveloping countries.245

However, this broad brush differentiation betweendeveloped and developing countries obscures the differ-ences that are emerging within these regions. Urbandevelopment and design initiatives in North America,Australia and New Zealand focus on compact city principlesand mixed developments to address the historical conditionsof suburban development and urban sprawl. However, trans-port-related initiatives are relatively rare, particularly interms of limiting and controlling the demand for individualmotorized transport and the development of mass transportsystems. This contrast with countries in Europe, where thereis a growing proliferation of examples to promote demand

The developmentand spread of international,national andregional municipal networkshas … provided akey driver formunicipal responsesin developedcountries

In developingcountries, mitigationinitiatives have alsooften been linkedwith adaptationresponses, takingadvantage of thepotential synergiesbetween both


Box 5.20 Obstacles to climate change mitigation actions in Durban, South Africa

For the municipality of Durban, responding to climate change is a major focus of the city’s commitment to sustainable development. Durbanwas one of the first African cities to participate in Local Governments for Sustainability’s (ICLEI’s) Cities for Climate Protection Campaign(CCP). However, the absence of policy coordination and the existence of competing socio-economic urban policy priorities stand in the wayof effectively delivering potential emissions reductions.

Early mitigation projects were landfill gas to electricity (resulting in reductions of 362,000 tonnes of CO2eq per year, or 2 per cent ofannual emissions), reduction of energy demand in municipal buildings (reductions of 914 tonnes of GHGs annually), and electricity frommicro-turbines integrated within the water piping systems, making use of Durban’s uneven topography. While setting municipal climate policyin motion, these initiatives did not result in significant emission reductions. A target of 27.6 per cent reductions by 2020 was proposed in the2008 Energy Strategy, to be achieved through the use of biofuels in transportation, the creation of residential green energy tariffs, a subsidizedresidential solar hot water programme, encouraging industrial efficiency, and the encouragement of local energy service companies.Implementing these would demand cross-cutting action across many municipal departments, as well as private partners.

However, projects have been held back by questions regarding who has the resources and the jurisdiction to implement them. Forinstance, the municipal Department for Environmental Management has the best understanding of the issue. However, it lacks both theresources and the mandate to act upon that knowledge (their remit being primarily biodiversity protection). The entity which is perhaps bestpositioned to act, the energy provider, is constrained by deeply engrained procedures and relationships (traditionally the intermediary buyingelectricity from the national grid and selling it on to local customers, they did not see local renewable energy generation within theirmandate). And the entity quickest to act, the Department for Water and Sanitation, while effective in making change in its own systems, doesnot have the desire or reach to coordinate broader changes. Therefore, while substantial opportunities for significant emissions reductionsexist, Durban’s experience shows that in the absence of integrated planning and streamlining of urban priorities, key barriers may be primarilyinstitutional, not technical.

Source: Aylett, 2010

management and enhancement in transport, while develop-ing or modernizing the public transport infrastructure. Citiesin Africa and Latin America and the Caribbean have empha-sized actions in urban infrastructure systems, particularly inthose cases in which upgrading the infrastructure alone canlead to significant gains, such as is the case in the wastemanagement system in Lagos (Nigeria).246 In these regions,there is evidence that measures being undertaken in thebuilt environment and urban development and designsectors are seeking to address issues of social equity.However, in Asia, new urban developments are emergingwhere high-income groups are able to create their owncommunities – often informed by green values in terms ofnature protection and resource conservation, but with lessregard for amelioration of social inequalities. Driven throughpartnerships of private and public agencies, large urbandevelopment projects that incorporate climate changemitigation concerns are taking place. However, concernshave been expressed about the impact and effectiveness ofsuch schemes in climate change terms, and also becausethey may have important environmental justice implicationsfor the social groups who are excluded from these partner-ships.

A third set of trends relates to the differences in theopportunities and constraints that municipal governmentsand other actors face in seeking to mitigate climate change.Clearly, the resources available to act upon climate changeare significantly different between cities in different regions,as well as between actors within individual cities. For manycities in developed countries a lack of resources is seen as acritical barrier to action, though these challenges are consid-erably higher for cities in developing countries. Analysis inthis chapter also suggests that a lack of expertise, of institu-tional capacity and of the ability to develop and enforcepolicy – as well as historic issues of underinvestment inurban infrastructures, informal settlements and persistentpoverty – pose significant challenges for cities in developingcountries seeking to address climate change mitigation. Theexample of Durban (see Box 5.20) explains the interaction ofmultiple obstacles to climate change mitigation in a city inSouth Africa. In order to address these issues, linkingclimate change actions with their potential co-benefitsappears to be crucial, particularly when these are linked withsocial and environmental justice objectives to improve thequality of life of the most disadvantaged sectors of thepopulation. Examples such as the Kuyasa housing project inCape Town (South Africa) and housing projects in BuenosAires (Argentina) and Rio de Janeiro (Brazil) are encouraging;but their prominence is still relatively low, particularly whencompared with the emphasis on the development of exclu-sive new urban developments. Furthermore, while inter-national policy instruments (such as the CDM), public–private partnerships and international networks may be ableto bring a degree of resource and support for climate changeactivities, there is, to date, mixed evidence of their impactupon fundamental issues of economic deprivation and socialinequalities. In developed countries, the impacts of focusingupon co-benefits are less clear cut. While such approachescan generate political support, they could also lead to the

watering down of climate change commitments or to a focusonly on those initiatives that can yield economic benefits inthe relatively short term, detracting attention from morefundamental issues concerning how (and by and for whom)energy is provided, the levels of personal mobility that canbe sustained, and the relationship between consumption,growth and climate change.

Despite the significant constraints facing urbanclimate change mitigation efforts, as the evidence docu-mented in this chapter illustrates, cities are taking importantmeasures to address the issue. The combined effects of insti-tutional structures, financial resources, the social andmaterial make-up of urban infrastructure networks, andpolitical support have created the capacity for significantadvances for climate change mitigation. This capacity is notonly unevenly distributed regionally and between differentcountries. Research also suggests that a growing divide maybe emerging between cities. Municipal governments andother urban actors with initial capacity in some cities areable to capitalize on opportunities for funding, political influ-ence, access to international organizations and internationalnetworks, and partnerships to build on their efforts, whileothers lack the wherewithal needed to access theseresources.247 Efforts by international networks, private-sector actors and international donor agencies to target asmall number of global and megacities as arenas withinwhich to mitigate climate change may exacerbate this divide.As a result, rather than being regionally differentiated,future urban climate change mitigation efforts may becharacterized by differences between an elite group of citieswith access to substantial resources, those (primarily indeveloped countries) who may be able to afford to undertakeinitiatives to pick the ‘low hanging fruit’, and the vast major-ity of cities for whom addressing climate change will remaina low priority. Furthermore, the channelling of resources inthis manner may also serve to support the interests of urbanelites rather than addressing broader issues of sustainabledevelopment and well-being. As discussed above, ensuringthat climate change mitigation can also address issues ofsocial and environmental justice will necessitate the partici-pation of a broad constituency of actors and, especially indeveloping countries, a focus on the multiple co-benefitsthat such initiatives could generate.

CONCLUDING REMARKSAND LESSONS FOR POLICYMitigating climate change is an increasingly pressing urbanissue. However, cities have very different starting points interms of their GHG emissions, related to issues of geogra-phy, political economy, infrastructure provision and socialpractices, and the capacity of governments, private organiza-tions and civil society actors. Historically, cities in developedcountries have contributed the vast majority of GHGemissions and bear the major responsibility to act. However,as GHG emissions begin to grow in some developingcountries, there is also a need to consider what appropriateand effective urban mitigation efforts might involve, and

A lack of expertise,of institutionalcapacity and of theability to developand enforce policy… pose significantchallenges for citiesin developingcountries seeking toaddress climatechange mitigation

Future urbanclimate changemitigation effortsmay be characterized bydifferences betweenan elite group ofcities with access tosubstantialresources …. andthe vast majority ofcities for whomaddressing climatechange will remain alow priority

Historically, cities indeveloped countrieshave contributed thevast majority ofGHG emissions andbear the majorresponsibility to act


how they might be combined with the more pressing issuesof urban adaptation.

This chapter suggests, in line with previousresearch,248 that efforts to mitigate climate change in citiesface a significant paradox. Those strategies which can beeffectively implemented may have the least impact, whilethose with the potential for the greatest reductions in GHGemissions may be the hardest to achieve. On the one hand,the most commonly implemented and effective strategiesare those which focus on reducing GHG emissions fromwithin the municipality (self-governing) and those which aimto improve energy efficiency. As noted in Figure 5.1, thewaste, transport and buildings sectors appear to be the ‘lowhanging fruits’ of urban GHG mitigations. It should,however, be kept in mind that the cost efficiency of inter-ventions within these sectors varies considerably (see Box5.17). This chapter suggests that the complex challengesfacing municipal governments – their partial autonomy incritical policy sectors, the splintering of urban infrastructurenetworks, the difficulties of meeting the basic needs ofurban citizens, and the controversial politics that accompanyefforts to divert from ‘business as usual’ – have limited theextent to which urban climate change governance hasextended beyond the areas of direct municipal control. Atthe same time, in contexts of competing aims and conflictingagendas, focusing on energy efficiency has been a meansthrough which urban actors have been able to address multi-ple agendas, including energy security, financial savings, airpollution and fuel poverty, alongside climate change.

However, there has, to date, been limited assessmentof the impact of such measures. While focusing on municipalGHG emissions alone will, in most cases, only account for asmall proportion of urban GHG emissions, energy efficiencymeasures have the potential to achieve significant savings.Examples of individual buildings, new urban developments,the retrofitting of energy-efficient technologies and behav-ioural programmes documented in this chapter havedemonstrated that energy efficiency could provide a crucialcomponent of urban efforts for climate change mitigation.Furthermore, such initiatives have often provided theimpetus for the development of comprehensive climatechange strategies, as the financial savings and political influ-

ence gained within the city drive more ambitious policy goalsand the development of additional measures. Nonetheless,such examples remain relatively small scale and isolated.Against a rising trend of energy consumption and GHGemissions, a critical question for future research and thedevelopment of policy is therefore the extent to which self-governing and energy efficiency initiatives can lead towidespread and sustained changes in the ways in whichenergy is used in cities.

On the other hand, measures which may have thegreatest impact upon urban GHG emissions, including theprovision of low-carbon and renewable energy infrastructuresystems, the reduction in demand for personal vehicle travel,as well as enabling and mobilizing actions by communitiesand stakeholders, have, to date, been less common. Whilethere are some promising signs that such initiatives aretaking place – in the development of new urban transitsystems in cities in developing countries, projects for urbanregeneration, and the growing involvement of a range ofprivate companies and community organizations – theseremain the exception rather than the rule. Evidence suggeststhat such initiatives are most likely to be successful whenthey demonstrate a range of additional economic, social andenvironmental benefits, and where they attract the supportof key urban actors. While this can be a progressive process,involving communities and stakeholders and addressingissues of social and environmental justice, it can also be onethat serves the interests of particular urban elites and leadsto a politics of exclusion.

Importantly, the evidence presented in this chaptersuggests that the potential for urban climate change mitiga-tion to address issues of social and economic equity is notpredetermined by the types of measure or governance mech-anisms deployed. For example, projects to generate energyfrom landfill sites can be undertaken as technical endeavourswith little regard for the impacts of such initiatives; but theycan also provide new forms of employment, sources offunding for investment in poor communities, and a means ofgenerating secure and affordable energy. Ensuring thatmitigating climate change does not come at the expense ofaddressing issues of inequity and justice is a criticalchallenge for future policy-making.

1 UNFCCC, 1992, Article 2.2 See Chapter 2 for details.3 IEA, 2008.4 Kern and Bulkeley, 2009.5 See also Chapter 2.6 Bulkeley, 2000; Betsill, 2001;

Bulkeley and Betsill, 2003;Kousky and Schneider, 2003;Yarnal et al, 2003; Allman et al,2004; Lindseth, 2004; Davies,2005; Mackie, 2005; Bulkeleyand Kern, 2006.

7 Dhakal, 2004, 2006; Bai, 2007;Holgate, 2007; Romero Lankao,2007b.

8 Sanchez-Rodriguez et al, 2008.9 Betsill and Bulkeley, 2007.

10 Satterthwaite, 2008a; Dodman,2009.

11 Harvey, 1996.12 Monstadt, 2009, p1927.13 Alber, 2010; Hemmati, 2008.14 See Chapter 3.15 See Chapters 4 and 6.16 IEA, 2009; UN, 2010.17 Sassen, 1991.18 Research undertaken in prepa-

ration for this chapter drawson a database of climatechange mitigation initiativestaking place in 100 cities. Forfurther information, seewww.geography.dur.ac.uk/projects/urbantransitions, last

accessed 21 October 2010.19 See section on ‘Urban gover-

nance for climate changemitigation’.

20 Kern and Alber, 2008, p4; seealso Jollands, 2008.

21 Kern and Alber, 2008, p3.22 ICLEI, 2006.23 Bulkeley and Kern, 2006; Betsill

and Bulkeley, 2007; Bulkeley etal, 2009.

24 Rutland and Aylett, 2008, p636.25 Owens, 1992; Banister et al,

1997; Capello et al, 1999;Norman et al, 2006; Lebel et al,2007. See also discussion onurban form and density in

Chapter 3.26 UN-Habitat, 2009a.27 UN-Habitat, 2010.28 UN-Habitat, 2009a.29 See UN-Habitat, 2009a.30 City of Cape Town, 2005; City

of São Paulo, 2009.31 For the example of Stockholm

(Sweden), see Holden andNorland, 2005.

32 Kolleeny, 2006 (Philadelphia);Energy Planning KnowledgeBase, undated (Manchester);A101, 2006 (Moscow); BCIL,2009 (India).

33 McGray, 2007.34 Ying, 2009.


NOTES

The waste, transportand buildingssectors appear to bethe ‘low hangingfruits’ of urban GHGmitigations

Ensuring thatmitigating climatechange does notcome at the expenseof addressing issuesof inequity andjustice is a criticalchallenge for futurepolicy-making

35 Moore, 2008.36 Schifferes, 2007.37 For example, the backing down

from implementing a plannedban on motorized privatevehicles on the islands.

38 Pearce, 2009.39 See also Box 2.7.40 BSHF Database (available at

www.worldhabitatarwards.org)(Boston and San Francisco);WHEDco, 1997 (New York).

41 Alber, 2010.42 Bulkeley et al, 2009, p43.43 Akinbami and Lawal, 2009;

Bulkeley et al, 2009.44 Foresight, 2008.45 Hemmati, 2008; Alber, 2010.46 Bulkeley et al, 2009, p44.47 This is discussed in more detail

in the section on ‘Urban gover-nance for climate changemitigation’.

48 See note 18.49 US Department of Energy,

2008.50 Pauzner, 2009.51 Boardman, 2007. For some

interesting examples of how todeal with existing buildingstock, see also http://thezero-prize.com, last accessed 18October 2010.

52 For example, innovation in theuse of traditional buildingmaterials in conventionalhousing in Bangalore (India)has been led by the pioneeringexperience and skills develop-ment promoted by architectChitra Viswanath (seewww.inika.com/chitra, lastaccessed 18 October 2010).

53 City of Cape Town, 2005;Ciudad de Mexico, 2008.

54 Bulkeley et al, 2009.55 Agencianova, 2009. This

project follows previousexperiences in sustainablebuilding, such as those led bythe architect Carlos Levintonfrom the Special Centre ofProduction and the Universityof Buenos Aires to createenergy-efficient buildingmaterials from recycledproducts (see Sotello, 2007).

56 Barry, 1943.57 Zhao and Michaelowa, 2006.58 Hemmati, 2008.59 Gender is a critical issue in

terms of behavioural patternsrelating to climate change.Although commentators havesuggested that women mayemit less GHGs emissions thanmen, the evidence is limited bythe lack of disaggregation ofdata about consumptionpatterns within the household.A study of consumptionpatterns in single-personhouseholds in differentEuropean countries supportedthe hypothesis that womenemit less GHG emissions thanmen (see Alber, 2010); butdoubts exist over whethersuch findings could be

extended over the whole lifeof individuals or could beapplied more generally indifferent types of householdsand different countries. On theother hand, women across theworld tend to have lowerincomes and greater participa-tion in the informal labourmarket. Even women who arenot living in poverty will tendto be less affluent and finan-cially secure than men; hence,they will have more modestconsumption associated withlower carbon footprints (Haighand Vallely, 2010).

60 OECD, 2008.61 Hemmati, 2008; Haigh and

Vallely, 2010.62 See also Aylett, 2010.63 Greene et al, 1999.64 Satterthwaite, 2008b, p11.65 Hemmati, 2008.66 UN-Habitat, 2008b.67 Graham and Marvin, 2001.68 See Chapter 2.69 See Bundesministerium für

Umwelt, Naturschutz undReaktorsicherheit (undated).

70 Bulkeley et al. 2009.71 City of Cape Town, 2005.72 Greenpeace, 2008; Wu and

Zhang, 2008.73 Greenpeace, 2008.74 Solar America Cities, 2009.75 See www.cleanenergy

fuels.com/main.html, lastaccessed 18 October 2010.

76 The scheme was funded by theDepartment for Environment,Food and Rural Affairs and theWaste Resources ActionProgramme.

77 Silver, 2010.78 See also see the sub-section on

‘Modes of public–privatecollaboration in urban climategovernance’ below.

79 See also Bulkeley et al, 2009;Aylett, 2010.

80 Oresanya, 2009.81 Ciudad de Mexico, 2008.82 Aylett, 2010.83 Ciudad de Mexico, 2008.84 Short et al, 2008; Bertaud et al,

2009. See also Chapter 3.85 Karekezi et al, 2003.86 World Bank, 2009c.87 Sari, 2007, p129.88 Sari, 2007, p137.89 Johnsson-Latham, 2007.90 Haigh and Vallely, 2010.91 Johnsson-Latham, 2007.92 Skutsch, 2002.93 Alber, 2010.94 See note 18.95 Wagner, 2009.96 See www.transmilenio.gov.co/

WebSite/English_Default.aspx,last accessed 18 October2010.

97 See www.cdm-egypt.org/, lastaccessed 18 October 2010.

98 The partnership is partlyfunded by the German federalgovernment’s Fuel Cell andHydrogen InnovationProgramme, and the partners

include Daimler, Shell, Total andVattenfall Europe.

99 Note that this measure isfrequently associated withimproving the air pollution ofthe city (e.g. Alam and Rabbani,2007).

100 Bertaud et al, 2009.101 Bertaud et al, 2009.102 See discussion in the sub-

section on ‘Urbaninfrastructures’ above.

103 Dlamini, 2006. The programmewas implemented with financialassistance of the governmentsof Norway and Denmark andthe World ConservationUnion (IUCN).

104 Lagos State Government, 2010.Updates about the tree-fellingprogramme can be found atwww.lagosstate.gov.ng, lastaccessed 18 October 2010.

105 Concejo de Bogotá, 2008.106 See Box 2.7.107 ICLEI Australia, 2008.108 This project is a collaboration

between the Clinton ClimateInitiative, MicrosoftCorporation, Autodesk andICLEI (Clinton Foundation,undated b).

109 See, for example, Bai, 2007;Dhakal, 2009.

110 UNEP et al, 2010. See also Box2.4.

111 Bulkeley and Kern, 2006.112 UN-Habitat, 2009a, p73.113 UN-Habitat, 2009a, p73.114 Bulkeley and Kern, 2006; Kern

and Alber, 2008; Bulkeley et al,2009.

115 Hammer, 2009.116 This trend is also reflected in

other arenas of climate changegovernance (see Biermann andPattberg, 2008; Bulkeley andNewell, 2010).

117 Jessop, 2002, p241; Sørensenand Torfing, 2007, 2009.

118 Bulkeley and Kern, 2006; Goreet al, 2009.

119 Martinot et al, 2009.120 Gore et al, 2009, p10.121 See the sub-section on

‘Public–private provision’below.

122 Bulkeley et al, 2009.123 State of São Paulo, 2008.124 GLA, 2008.125 Bulkeley and Schroeder, 2008;

www.nabers.com.au, lastaccessed 22 October 2010.

126 Bulkeley et al, 2009.127 Bulkeley and Kern, 2006;

Bulkeley et al, 2009; Gore et al,2009; Hammer, 2009.

128 Bulkeley et al, 2009.129 Funded by the Danish

International DevelopmentAgency.

130 Aylett, 2010.131 See note 18.132 UNEP, 2007, p44.133 In the eastern US, for example,

local planning regulations haveslowed the establishment ofhydrogen refuelling stations.

134 Bulkeley et al, 2009.

135 Aylett, 2010.136 UN-Habitat, 2009a, p74.137 UNEP, 2007, p46.138 See the sub-section on ‘Modes

of governing climate changemitigation’.

139 UN-Habitat, 2007, p106.140 Satterthwaite et al, 2009b, p24.141 Bulkeley and Newell, 2010.142 See www.carbon

rationing.org.uk, last accessed18 October 2010.

143 Peak oil is the point in timewhen the maximum rate ofglobal petroleum extraction isreached, after which the rate ofproduction enters terminaldecline.

144 See www.transitionnetwork.org, last accessed 18 October 2010.

145 Pers comm, 2010.146 See the sub-section on

‘Provision’ above.147 See the sub-section on ‘Urban

infrastructures’ above.148 The London Energy Service

Company is a ‘private limitedcompany with shareholdingsjointly owned by the LondonClimate Change Agency Ltd(with a 19 per cent sharehold-ing) and EDF Energy (Projects)Ltd (with an 81 per cent share-holding)’ (LCCA, 2007, pp5–6).

149 Clinton Foundation, undated b.150 See Chapter 2.151 The Climate Group is an inter-

national non-profitorganization whose membersinclude national, regional andlocal governments, as well asprivate corporations (seewww.theclimategroup.org/about-us/, last accessed 18October 2010).

152 Bulkeley and Betsill, 2003;Romero Lankao, 2007b;Biermann and Pattberg, 2008;Rutland and Aylett, 2008.

153 Kern and Alber, 2008.154 Betsill and Bulkeley, 2007;

Bulkeley et al, 2009; RomeroLankao, 2008.

155 Deangelo and Harvey, 1998;Bulkeley et al, 2009; Hammer,2009.

156 Granberg and Elander, 2007,p545.

157 Qi et al, 2008, pp397–398.158 Hammer, 2009.159 Betsill and Bulkeley, 2007;

Bulkeley et al, 2009; Puppim deOliveira, 2009.

160 Bai, 2007; see also Bulkeley andKern, 2006; Granberg andElander, 2007.

161 Collier, 1997; Lebel et al, 2007;Jollands, 2008; Schreurs, 2008;Sugiyama and Takeuchi, 2008;Setzer, 2009.

162 GLA, 2007, p19.163 Monni and Raes, 2008, p753.164 Sugiyama and Takeuchi, 2008,

p429.165 Satterthwaite, 2008b, p9.166 See the sub-section on ‘Self-

governing’ above.167 Romero Lankao, 2007b, p529.


168 Kern and Alber, 2008.169 Bulkeley et al, 2009, p23.170 Holgate, 2007.171 OECD, 2008, p24; see also Bai,

2007; Crass, 2008; Kern andAlber, 2008.

172 Kern and Alber, 2008, p4.173 Betsill and Bulkeley, 2007, p450.174 Akinbami and Lawal, 2009, p12.175 Schwaiger and Kopets, 2009.176 UNEP, 2007.177 Bulkeley et al, 2009, p49.178 Sari, 2007, p141.179 Satterthwaite, 2008b, p12.180 Sippel and Michaelowa, 2009.181 See www.cdmgold

standard.org/, last accessed 18 October 2010.

182 GLA, 2007, p19.183 Arup, 2008.184 See Chapter 3.185 Newcastle City Council, 2008.186 Allman et al, 2004; Lebel et al,

2007; Sugiyama and Takeuchi,2008, p432.

187 Aylett, 2010.188 Akinbami and Lawal, 2009.189 Akin to previous definitions of

large technical systems; seeHughes, 1989.

190 Bertaud et al, 2009, p23.191 Bertaud et al, 2009.192 Schwaiger and Kopets, 2009,

p3.193 Akinbami and Lawal, 2009, p10.194 Monni and Raes, 2008, p749.195 Hodson and Marvin, 2007.196 See www.climate-change.ir/en/,

last accessed 17 May 2010.197 Satterthwaite, 2008a, p11.198 Castán Broto et al, 2007, 2009.

199 Kern and Bulkeley, 2009.200 Setzer, 2009, p8.201 Jollands, 2008, p5.202 Bulkeley and Kern, 2006.203 Sugiyama and Takeuchi, 2008,

p430.204 The Carbon Finance Capacity

Building Programme is aninitiative of the World Bank,ECOS, C40, the SwissGovernment (SECO) and theCanton of Basel City.

205 See www.lowcarboncities.info/home.html, last accessed 18 October 2010.

206 Kern and Alber, 2008; Jollands,2008.

207 To date, there is little evidenceof the role of the voluntarycarbon market in urban climatechange governance and thisanalysis focuses on the CDM.

208 Puppim de Oliveira, 2009,p257. See also Box 3.3.

209 See City of Cape Town, 2005.210 For an overview of this debate,

see Bumpus and Liverman,2008.

211 World Bank, 2010a. 212 World Bank, 2010c.213 Sippel and Michaelowa, 2009;

Roberts et al, 2009, p13; ICLEI,2010; Clapp et al, 2010.

214 Roberts et al, 2009, p14.215 World Bank, 2010a.216 ‘Policy entrepreneurs’, individu-

als involved in the innovationof policies or schemes, aredefined by ‘their willingness toinvest their resources – time,energy, reputation, and

sometimes money – in thehope of a future return ... inthe form of policies of whichthey approve, satisfaction fromparticipation, or even personalaggrandizement in the form ofjob security or career promo-tion’ (Kingdon, 1984, p122).‘Political champions’ areindividuals who advocate theimportance of responding toclimate change and who mayback particular policies,projects or schemes. SeeBulkeley and Betsill, 2003;Bulkeley and Kern, 2006; Qi etal, 2008; Schreurs, 2008.

217 Bulkeley and Kern, 2006,p2253.

218 Romero Lankao, 2007b; Setzer,2009; Aylett, 2010.

219 See www.c40cities.org/, lastaccessed 18 October 2010.

220 See www.theclimategroup.org/our-news/news/2009/2/24/the-climate-group-launches-forward-chicago/, lastaccessed 22 October 2010.

221 City of Cape Town, 2006.222 Puppim de Oliveira, 2009,

p254.223 Frayssinet, 2009.224 Bai, 2007; Gore et al, 2009;

Betsill and Bulkeley, 2007.225 Qi et al, 2008, p393.226 Bartlett et al, 2009, p22; see

also McGranahan andSatterthwaite, 2000.

227 Bai, 2007.228 Puppim de Oliveira, 2009, p25;

see also Bai, 2007; Romero

Lankao, 2007b; Jollands, 2008.229 See Chapter 3.230 Lasco et al, 2007, p84.231 Bartlett et al, 2009.232 See Chapter 6.233 Bartlett et al, 2009.234 Urvashi Devidayal, the Climate

Group, pers comm, 2010.235 Zahran et al, 2008.236 Bulkeley and Betsill, 2003.237 Flyvbjerg, 2002.238 Rutland and Aylett 2008, p636.239 Hoffman, 2011.240 See the sub-section on

‘Municipal policy approaches’above.

241 The Philippines adopted aNational Framework Strategyon Climate Change in April2010 (www.climatechangecom-mission.gov.ph/link/downloads/nfscc/index.php, last accessed10 August 2010.

242 Demetriades and Esplen, 2008;Alber, 2010.

243 See the sub-section on ‘Multi-level governance’ above.

244 See Chapter 6.245 See note 18.246 Oresanya, 2009.247 Granberg and Elander, 2007;

Kern and Bulkeley, 2009.248 For example, Bulkeley and

Betsill, 2003; Bulkeley andKern, 2006; Bai, 2007; Betsilland Bulkeley, 2007; Rutland andAylett, 2008; Bulkeley et al,2009; Gore et al, 2009.


The lives and livelihoods of hundreds of millions of peoplewill be affected by what is done (or not done) in urbancentres with regard to adapting to climate change over thenext decade. Action is urgently needed, both to addresscurrent risks and to begin building into urban fabrics andsystems resilience to likely future risks. Most urban build-ings and infrastructure are long lived; thus, what is designedand built now will have to cope with climate change manydecades into the future. As a result, it is generally mucheasier to make provisions now for likely future climate-related risks – in infrastructure expansion, new buildingsand new urban developments – than to have to retrofit build-ings, redo infrastructure and readjust settlement layouts inthe future.

As noted in Chapter 4, urban centres already concen-trate a large proportion of those most at risk from the effectsof climate change. This includes a high proportion of urbancentres with very large deficits in infrastructure, as well as inthe institutional and financial capacity needed to reducethese risks. Urban centres also concentrate the enterprisesthat generate most of the world’s gross domestic product(GDP) and provide livelihoods for around two-thirds of theworld’s economically active population.1 In most urbancentres, buildings, infrastructure and services will have tocope with an increasing scale and range of climate impacts.Furthermore, as most of the growth in the world’s popula-tion over the next few decades will occur in the urbancentres of developing countries2 – many (if not most) ofwhich are already unable to provide adequate living condi-tions for their populations – it is likely that a majorproportion of these new urban residents will be living insettlements that do not have the needed resilience toclimate change.

Yet, adapting urban areas to climate change is not anew ‘standalone’ task or responsibility that can be allocatedto one single stakeholder. It requires changes in the waysthat almost all sectors of government, business and house-holds behave and invest. In addition, much of what is neededto make cities resilient to climate change within the nextfew decades is no more than ‘good development’ in thesense of the infrastructure, institutions and services thatmeet daily needs and reduce disaster risk. As this chapterdiscusses, however, this is not easily achieved, as particular

institutions and funding sources are given responsibilities for‘climate change adaptation’ not for ‘development that incor-porates climate change adaptation’. Many discussions ofclimate change adaptation start with a discussion of the risksthat climate change is bringing or may bring and thenconsider what needs to be done to address this – withoutconsidering how the climate change-related risks fit withinother risks. What most urban centres in developingcountries need is not a climate change adaptation prog-ramme but a development programme – meeting alreadyexisting deficits in provision for water, sanitation, drainage,electricity, tenure, healthcare, emergency services, schools,public transport, etc. – within which measures for climatechange adaptation are integrated.

The first section of this chapter discusses what ismeant by adaptation, adaptive capacity and similar terms, asapplied to urban centres. The second section reviews house-hold and community responses to the impacts of climatechange and highlights the major challenges to community-based climate change adaptation. This is followed in thethird section by a similar review of the responses by city andmunicipal governments. This review provides the basis for adiscussion in the fourth section of the main issues that needto be addressed to develop effective city-based climatechange adaptation strategies. The fifth and sixth sectionsdiscuss the financing and other key challenges of urbanclimate change adaptation, respectively. The final sectionprovides some concluding remarks and lessons for policy.

UNDERSTANDINGADAPTATIONIt is important that there is clarity in what is meant byadaptation, adaptive capacity and adaptation deficit. Drawingon the definitions of the Intergovernmental Panel on ClimateChange (IPCC),3 adaptation to (human-induced, or ‘anthro-pogenic’) climate change is understood to include all actionsto reduce the vulnerability of a system (e.g. a city), popula-tion group (e.g. a vulnerable population in a city) or anindividual or household to the adverse impacts of anticipatedclimate change. Adaptation to climate variability consists ofactions to reduce vulnerability to short-term climate shocks

It is … much easierto make provisionsnow for likely futureclimate-related risks… than to have toretrofit buildings,redo infrastructureand readjust settlement layoutsin the future

Adapting urbanareas to climatechange … requireschanges in the waysthat almost allsectors of government,business and households behaveand invest

What most urbancentres in develop-ing countries need is… a developmentprogramme …within whichmeasures for climatechange adaptationare integrated

C H A P T E R

CLIMATE CHANGE ADAPTATIONRESPONSES IN URBAN AREAS

6

(whether or not these are influenced by climate change) –for instance, as a city government ensures that the drainagesystem can cope with monsoon rains. Most of the measuresfor adapting to climate variability (which will be taking placein most well-governed cities) will also contribute to climatechange adaptation (as a co-benefit).

The outcome of successful adaptation is resilience –and is a product of governments, enterprises, civil societyorganizations, households and individuals with strongadaptive capacity.4 For cities or particular urban neighbour-hoods, it indicates a capacity to maintain core functions inthe face of hazard threats and impacts, especially for vulnera-ble populations. It usually requires a capacity to anticipateclimate change and plan needed adaptations. The resilienceof any population group to climate change interacts with itsresilience to other dynamic pressures, including economicchange, conflict and violence.

Adaptive capacity is the inherent capacity of a system(e.g. a city government), population (e.g. a low-incomecommunity in a city) or individual/household to undertakeactions that can help to avoid loss and can speed recoveryfrom any impact of climate change. Adaptive capacity is theopposite of vulnerability.5 The risks that have to be reducedby adaptation can be direct, as in larger and/or morefrequent floods, or more intense and/or frequent storms orheat waves; or less direct, as climate change negativelyaffects livelihoods or food supplies (and prices), or access towater needed for domestic consumption or livelihoods.Certain groups may face increased risks or costs frommeasures taken in response to climate change – includingadaptation measures (e.g. measures to protect particularareas of a city from flooding that increase flood risks ‘down-stream’) and mitigation measures (e.g. a greater emphasis onnew hydropower schemes that displace large numbers ofpeople from their homes and livelihoods).

Elements of adaptive capacity include knowledge,institutional capacity, and financial and technologicalresources. Low-income populations in a city will tend to have lower adaptive capacity than high-income populationsbecause of their lower capacity to afford good-qualityhousing on safe sites. There is also a wide range among cityand national governments in their adaptive capacities, relat-ing to the resources available to them, the information baseto guide action, the infrastructure in place, and the quality oftheir institutions and governance systems.

The lack of adaptive capacity to deal with problemscaused by climate variability and climate change is stronglyrelated to the scale of what can be termed the adaptationdeficit: the deficit in infrastructure and service provision andin the institutional and governance system that is meant tobe in place to ensure adaptation. Of course, this dependsheavily on the competence and capacity of local govern-ments and the quality of the relations between localgovernment and populations at risk within their jurisdiction.In many developing country cities, the main problem is thelack of provision of basic city infrastructure and the lack ofcapacity to address this. This is one of the central issues withregard to urban climate change adaptation because mostdiscussions on this issue focus on needed adjustments to

infrastructure to climate-proof it. However, cities cannotclimate-proof infrastructure that is not there. In addition,new sources of funding for climate change adaptation havelittle value if there is no local capacity to design, implementand maintain the needed adaptation measures, or no interestwithin local government in working with the populationsmost at risk (which in many urban contexts, as noted inChapter 4, are concentrated among low-income householdsliving in informal settlements and slums).

Ultimately, the most important and effective form ofadaptation is to stop the process that generates increasinglevels of hazard and risk – that is, to slow the growth of, haltand then reduce greenhouse gas (GHG) emissions or othermeasures to reduce global warming (i.e. mitigation).6 Failureto mitigate will lead to the failure of adaptation, as climatechange risks become increasingly severe. So adaptation andmitigation are not alternative strategies, but complementaryones that need to be pursued together.

It was the failure of the world’s governments to reachagreement to reduce GHG emissions during the 1990s thathas made the need to greatly increase adaptation capacity sourgent. It is now too late to stop the increase in climatechange-related hazards in the short term. Even if the world’sgovernments do reach agreement on the need for rapidreductions in global GHG emissions and actually implementthe measures needed to achieve this, the GHG emissionsalready generated and the time-lags in global systems7 stillmean increasing hazard and risk levels for most urbancentres – and, therefore, an increasing need to adapt.Adaptation can reduce the adverse impacts of climate changeconsiderably; but, generally, it cannot remove all adverseimpacts – especially if the needed agreements to reduceglobal emissions have not been achieved. So there are limitsto what adaptation can protect. There will also be an increas-ing number of locations that become permanently beyondadaptation – because the needed measures to protect themare considered too expensive (e.g. particular coastal zonesinundated by sea-level rise) or technically unfeasible. Suchconsequences are often referred to as residual damage, andthe number of such locations (and populations at risk) islikely to rise without successful mitigation (see Figure 6.4).

As described in more detail later in this chapter,adaptation can be undertaken by different actors – forinstance, by individuals, households and commercial enter-prises. This may be within government programmes orcompletely independent of government (in which case it isgenerally referred to as autonomous adaptation). Differentlevels of government (from national through regional andcity-wide to district or ward) and different sectors of govern-ment have responsibility for many of the needed adaptationsor for providing the regulatory framework – or the carrots orsticks – to encourage other actors to adapt. Adaptations thatare planned in anticipation of potential climate change aretermed planned adaptation. Generally, government agencieshave the responsibility to provide information about currentand future risks, and provide frameworks that supportindividual, household, community and private-sector adapta-tion. However, governments often do not fulfil this role, andcommunity-based and other civil society organizations may

The outcome ofsuccessful adaptation isresilience

The lack of adaptivecapacity to deal withproblems caused byclimate variabilityand climate changeis … related to thescale of … theadaptation deficit

The most importantand effective formof adaptation is tostop the process thatgenerates increasinglevels of hazard andrisk (i.e. mitigation)


be the initiators and supporters of planned adaptation. Ashas long been evident in initiatives to improve conditions ininformal settlements, a proactive civil society may berequired to galvanize government and to demonstrate whatcan be achieved.8

In recognition of the fact that much adaptation toclimate variability (and climate change) takes place throughthe conscious efforts of particular communities, the IPCChas highlighted the importance of what is termed commu-nity-based adaptation. As discussed in more detail in a latersection,9 community-based adaptation has particular impor-tance where local governments lack adaptive capacity. Yet, italso has importance within effective local government-drivenadaptation because of the knowledge and capacity that it cancontribute. For urban areas, there is a danger that itsrelevance will be both overstated and underplayed at thesame time. On the one hand, it will be overstated becausecommunity-based organization and action cannot provide thecity-wide infrastructure and service provision and city-regionecosystem services protection and management that are socentral to effective adaptation. On the other hand, however,the importance and effectiveness of community-basedadaptation can be underplayed as the policies and practicesof governments and international agencies fail to recognizethe capacity of community-based organizations to contributeto adaptation or, if they do, they lack the institutional meansto support them.10

There are also actions and investments that increaserather than reduce risk and vulnerability to the impacts ofclimate change and these are termed maladaptation.Examples of this include the shifting of risk from one socialgroup or place to another; it also includes shifting risk andcosts to future generations and/or to ecosystems and ecosys-tem services. Many investments being made in cities are, infact, maladaptive rather than adaptive, as they decreaseresilience to climate change. Indeed, the very process of‘unmanaged’ urban expansion usually brings with it increas-ing risk as inappropriate sites are developed and asinfrastructure provision fails to keep up. Removing maladapta-tions and the factors that underpin them are often among thefirst tasks to be addressed before new adaptations.

HOUSEHOLD ANDCOMMUNITY RESPONSESTO THE IMPACTS OFCLIMATE CHANGENational governments are meant to represent the interestsof their citizens in international discussions on allocatingresponsibility for climate change mitigation and in develop-ing international funding sources and institutions and otherforms of support for adaptation. Similarly, local (metropoli-tan, city and municipal) governments are, in principle,responsible for implementing climate change adaptationmeasures at the local level.

However, risk reduction and resilience to risk alsodepend on actions taken by households and by community-

based organizations. And for a large section of the urbanpopulation in developing countries, little can be expected oflocal and national governments as they currently lack thecapacity or willingness to provide the basic infrastructureand services that are central to adaptation.

Where local governments are weak or ineffective,household and community strategies become more impor-tant for reducing climate change risks and impacts in urbanareas. In such situations, urban residents have long had tocope with a wide range of risks to their lives and livelihoods.Many of the measures that they take to cope with risk areresponses to extreme weather, including flooding, extremetemperatures and landslides – although the root cause of therisk is often far more related to the lack of infrastructure orthe lack of safer sites that they can afford. In many locations,household and community strategies have developed overyears or even decades to prevent loss of life and damage toproperty. Yet, they have very limited capacities to substitutefor government investments in ‘hard’ infrastructure, whichis essential for risk reduction. Since these responses aregenerally small scale and cannot address the underlying rootcauses of vulnerability,11 they have frequently been ignored.However, supporting these local responses should be oneaspect of an overall adaptation strategy for urban areas. Indoing so, these coping strategies can be enhanced to ensurethat the investments made by low-income urban residentscontribute to building their resilience.

Studies in informal settlements exemplify the impor-tance of what individuals and households do for themselves– and, for many of these, the importance of family andsometimes of friends and neighbours in providing help. Thisrange of measures taken to help cope with extreme eventscan be divided into two:

• those that are preventive (that remove the hazard orexposure to it); and

• those that are impact minimizing or impact reducing(better quality defences against the hazard or assets thathelp recovery).12

The discussion below starts by reviewing examples of house-hold and community responses to climate change, andconcludes with an assessment of challenges to household-and community-based adaptation.

Household responses

Individuals and households take measures to reduce risksfrom extreme weather events such as flooding or extremetemperatures. Likewise, wealth helps individuals or house-holds to buy their way out of risks – for instance, by beingable to buy, build or rent homes that can withstand extremeweather in locations that are less at risk from flooding.Higher-income groups can also afford the measures that helpthem to cope with illness or injury when they are affected(the medical treatment needed, taking time off work) orwhen their assets are damaged (e.g. through compensationfrom insurance). Many of these measures also reduce risksfor a wide range of hazards; a good-quality secure home with

Where local governments areweak or ineffective,household andcommunity strategies becomemore important forreducing climatechange risks andimpacts in urbanareas

Supporting … localresponses should beone aspect of anoverall adaptationstrategy for urbanareas

131Climate Change Adaptation Responses in Urban Areas

good infrastructure and services removes or greatly reducesa great range of risks, including most of those related toclimate change. Savings schemes can be drawn on to helpcope with a wide range of stresses or shocks, including thosearising from extreme weather.

Those unable to get or afford these take othermeasures to reduce the impacts of hazards that they cannotavoid. These can be seen as contributing to adaptation inthat they reduce vulnerability to hazards,13 and many can beconsidered as strategies in that they include a coherentrange of measures that respond to changes in risk levels. Astudy of this in Indore (India) showed the complex andvaried measures by which low-income households living inareas often flooded adapted to flooding.14 They wereprepared to live in homes that flooded regularly because ofother advantages that these sites provided – namely, accessto low-cost housing, and central city locations close to jobs,to markets for the goods that they made or collected (manyearn a living collecting waste), and to health services,schools, electricity and water. Households and enterprisestook both temporary and permanent measures to minimizethe impacts of flooding – for instance, by raising plinthlevels, using flood-resistant building materials, choosingfurniture that is less likely to be washed away, and ensuringthat shelving and electric wiring are high up the walls,above expected water levels. Many households hadsuitcases ready, so valuables could be carried to higherground when floodwaters are rising, and contingency plansfor evacuating persons and possessions (e.g. first to movechildren, older persons and animals to higher ground, thento move electrical goods, then lighter valuables and cookingutensils):

When we see very dark clouds up the hills, weexpect heavy rains to come. So we get ourselvesprepared by transferring our valuable things onour very high beds which are reached by climb-

ing ladders. Also, children who sleep on thefloor are transferred to the high beds.15

More established residents had also learned how to getcompensation from the government for flood damage. Noneof these measures reduced the flooding; but they certainlyreduced the impacts of flooding upon health, assets andlivelihoods.

In Lagos (Nigeria), a city with very large deficits ininfrastructure and large sections of the population at riskfrom flooding (see Box 6.1), interviews with the inhabitantsof four informal settlements close to the coast showed thatthey considered flooding as their most serious problem,although flood risks varied by settlement and within eachsettlement.

A study in Korail (Bangladesh) documented a range ofhousehold measures to reduce loss from flooding and hightemperatures and facilitate recovery (see Box 6.2). Similarly,a study of flooding problems faced by residents of low-incomecommunities in Accra (Ghana), Kampala (Uganda), Lagos(Nigeria), Maputo (Mozambique) and Nairobi (Kenya)16

showed a comparable mix of measures to reduce impacts. InNairobi’s informal settlements (where around half the city’spopulation live), responses to flooding included bailing waterout of houses, putting children on tables and, if necessary,moving them to nearby unaffected dwellings, diggingtrenches around houses, constructing temporary dykes ortrenches to divert water away from the house, and a range ofways to stop water from coming into homes. Residents alsomoved to higher ground as floodwaters rose. Similarmeasures were taken by households in Accra, Lagos andKampala. In addition, in Kampala, some residents undertookcollective work to open up drainage channels. In Lagos, oneresident stated the following: ‘There has not been assistancefrom anyone. Neighbours cannot assist because everybody ispoor and vulnerable. I am planning to quit this place becauseit is horrible living here.’17

Low-income households … wereprepared to live inhomes that floodedregularly because ofother advantagesthat these sitesprovided – namely,access to low-costhousing, and centralcity locations


Box 6.1 Household and community responses to flooding in informal settlements in Lagos, Nigeria

The location of Lagos on a narrow low-lying coastal stretch bordering the Atlantic Ocean puts it at risk from sea-level rise and storm surges.However, it is the lack of attention by state and local governments to the needed storm and surface drains and other infrastructure, and alsoto land-use management, that has created most of the risks from flooding. The city has expanded rapidly and much of the population growthhas been housed in informal settlements in marshy areas or near the lagoons. Many new urban developments have taken place on floodplains(as mangroves have been cleared and wetlands filled) or on stilts over the lagoon.

Interviews with inhabitants of four informal settlements close to the coast showed that flooding was the most serious problem thatthey faced, although flood risks varied by settlement and within each settlement. In one of the communities (Makoko), for instance, residentsliving next to a channel were more severely affected than other residents. Floodwaters almost always entered homes and floods lasted for upto four days. Over 80 per cent of respondents reported that they had been flooded three or four times during 2008. Most interviewees listedthe poor drainage system as the main cause of the floods, with the effects of ‘overpopulation’ also listed in terms of more household wastesdisposed on streets or in drains and the encroachment of drainage channels by buildings.

Almost all respondents highlighted the shortages of potable water after flooding, with 91 per cent mentioning the impacts of floodingupon their health and increased medical expenses. Most also noted how floods deny them job opportunities. There were some communityinitiatives to clear blocked drainage channels; but most responses were by households as they constructed drains, trenches or walls to try toprotect their houses or filling rooms with sand or sawdust. Foodstuffs and other household items were also stored on shelves or cupboardsabove anticipated flood levels. Three-quarters of respondents received assistance from family and friends after flood events; far fewer receivedassistance from government or religious organizations.

Source: Adelekan, 2010

In Dar es Salaam (Tanzania), residents in Tandale(Kinondoni Municipality) take a range of measures to protectthemselves and their houses when flooding occurs. Theseinclude temporary relocation and placing easily damageditems (such as mattresses) in the ceiling areas of houses.Some households have constructed additional walls aroundtheir houses to prevent floodwater from entering.18

The above examples show that most householdresponses are impact-reducing, ad hoc, individual short-termefforts to save lives (e.g. to sleep on high tables or wardrobesand move family members to safer sites), or to protectproperty (e.g. making barriers to water entry at the door,digging trenches to steer water away from the door, makingoutlets at the rear of the house so water flows out quickly).

Community responses

Community-based adaptation is a process that recognizes theimportance of local adaptive capacity and the involvement oflocal residents and their community organizations in facilitat-ing adaptation to climate change.19 The starting point forcommunity-based adaptation is the individual and collectiveneeds of the residents in a community and their knowledgeand capacities. It is based on the premise that local commu-nities have the skills, experience, local knowledge andmotivation, and that – through community organizations ornetworks – they can undertake locally appropriate riskreduction activities that increase resilience to a range offactors, including climate change.20 It also recognizes (orassumes) a capacity among the residents in any ‘community’to work together. The central principles of community-based

adaptation are that it works at the level of the community: itis about communities making choices rather than havingthem imposed from outside. Advocates of community-basedadaptation question the value and effectiveness of top-downadaptation approaches as they see the difficulties of gettingthese to be pro-poor, locally appropriate and locally account-able.

Community-based adaptation to extreme weather,water constraints or other risks to which climate changecontributes is a pragmatic recognition of the limitations orinadequacies of government action on adaptation. It may bethe responsibility of government to provide and maintaininfrastructure that can deal with extreme events; but forthose areas and populations inadequately served by these,community responses can play a significant role in reducingrisks or impacts. As such, community-based preparedness isan important part of resilience to extreme weather eventswhose timing and magnitude are likely to become lesspredictable as a result of climate change.

To date, community-based adaptation has primarilybeen practised in rural areas. However, communities inurban areas can also have an important role in determiningthe most effective responses to help them address thechallenges of climate change. For instance, over the last fewyears, a growing number of studies have examined theresponses of low-income households and communities livingin informal settlements to extreme weather-related risks,especially floods. In the four informal settlements of Lagos(Nigeria) described above that have to cope with regularflooding (see Box 6.1), there were some community initia-tives to clear blocked drainage channels, although most

The starting pointfor community-based adaptation isthe individual andcollective needs ofthe residents in acommunity andtheir knowledge andcapacities


Box 6.2 Household responses to reducing risks from flooding in Korail, Bangladesh

Korail is one of the largest informal settlements in Dhaka (Bangladesh). It covers 90 acres (36.4ha) and has a population of more than100,000. When the site was first settled it occupied the high ground; but as the population expanded, houses were built closer to or evenover the water of the adjacent lake and reservoir. Despite the risks, this is considered a good location for employment by its residents, as it isnear high-end residential and commercial areas. It thus attracts people mostly in service jobs such as cleaners, rickshaw pullers and workersin ready-made garment industries.

Interviews with households living near the water’s edge and on higher ground focused on their experience of climate variability,hazards and coping strategies. Those interviewed highlighted how any climate hazard reduces earnings through missed working hours or evendays. They took action in response to flooding and water clogging and in response to rainfall that was anticipated (e.g. the regular monsoonrains) and unexpected. Before heavy rainfall, some moved to safer locations. This was not an option for most residents though, as it meantlosing assets, disrupting livelihoods and losing the right to stay and live in that location. Most impact-minimizing actions were part of regularpractice – for instance, making barriers across door fronts, increasing furniture height (e.g. putting them onto bricks), making higher plinthsand arranging higher storage facilities (e.g. placing shelves higher up on the walls). To help cope with very high temperatures, creepers weregrown in courtyards to cover roofs and other materials are put on roofs to reduce heat gain; most households used some form of falseceiling or canopy made out of cloth (a popular practice in rural areas, adopted in urban houses).

For houses near or on the water’s edge, structures are on stilts, with platforms constructed higher up the stilts. These also havebetter ventilation than houses inland. Wooden planks for flooring are preferred as they suffer less from water clogging once floods subsideafter heavy rainfall. Stilts also mean expansion is possible over the lake. During flooding or water clogging, most residents sleep on furniture,use moveable cookers for food preparation (that can be used on shelves or on top of furniture); some shared services with unaffected neigh-bours. Other measures include making outlets to help get the floodwater out of the house.

Half the households interviewed save regularly with community-savings groups or non-governmental organizations (NGOs), andsavings were important for coping with flood impacts. Many households also bought building materials throughout the year so they had theseto use in rebuilding, after flooding. Half the households reported that they feel able to ask relatives or friends for help after a disaster.

Source: Jabeen et al, 2010

actions were taken by households. The same is true in Korail(Bangladesh), although some households had taken part ininitiatives to clean and clear drains (see Box 6.2).

In practice, the development of infrastructure whichreduces climate change impacts is often beyond the capabili-ties of even the best organized and most representativecommunity organizations. For example, developing adrainage system that actually stops or greatly reduces flood-ing – especially in high-density settlements on high-risk siteswith little or no drainage infrastructure and space for newinfrastructure – is usually beyond the means of communityorganizations. This is not to say that it cannot be done;community-directed slum and squatter upgrading hasachieved this; but this is where they get appropriate supportfrom government, as in the Baan Mankong (Secure Tenure)programme in Thailand.21 The Orangi Pilot Project Researchand Training Institute (in Karachi, Pakistan) has also demon-strated that households in informal settlements can jointogether to fund and manage the installation of sewers anddrains and do so at scale.22 However, this was facilitated bythe fact that most informal settlements in Pakistan’s urbanareas developed with grid layouts and space for roads andpaths (under which the sewers and drains could beinstalled). In addition, the local government’s water andsanitation authority came to support this by providing thetrunk sewers and drains into which the neighbourhoodinitiatives could be integrated. What these and other casesshow is how effective risk reduction is possible if household,community and government investments and actions worktogether in a coordinated manner.

This point is illustrated by discussions with twocommunities that had experienced serious floods and withemergency managers in the two urban communities ofMansión del Sapo and Maternillo, located in the north-eastern municipality of Fajardo in Puerto Rico.23 Thesediscussions focused on flood hazards, causes and possiblesolutions. They showed good community knowledge of floodhazards (each community produced a map of the extent of flooding) and its causes. However, the residents’ maps differed from those of the emergency managers –especially highlighting the risks for those living close to adrainage channel. They also differed in terms of sources of floodwaters (residents included urban runoff, whereas theemergency managers only considered river overflow).24 Bothcommunities highlighted solutions that were beyond theirown capacities and that set responsibility for addressing theproblems with government. Yet, the problem here was boththe limitations in what government was likely to do and thelimitations in the technical solutions proposed. From a floodrisk reduction perspective, it was important to have astronger community engagement that recognized the needfor disaster preparedness because of the limits in what thestructural measures that government undertakes or shouldundertake could achieve. This community engagementshould include monitoring local conditions that can causefloods or exacerbate their impacts and acting on this (e.g.drainage channel maintenance) and flood preparation plans(including, where needed, plans for evacuations). Here,resilience to climate change depends not only on technical

measures and structural solutions, but also on householdand community capacity to cope better with extremeweather events that are less predictable in their magnitudeand timing. This is a point that has relevance for most urbancentres and settings.

The constraints on community capacity in theabsence of government support are highlighted by a study of15 disaster-prone slums in El Salvador. Here, too, there was amix of household and community responses to climatechange-related risks. Households recognized that floodingand landslides were the most serious risks to their lives andlivelihoods, although earthquakes and windstorms, lack ofjob opportunities, and water provision and insecurity fromviolent juvenile crimes were also highlighted. They investedin risk reduction, for instance, by improving their homes,diversifying their livelihoods or having assets that could besold if a disaster occurred. Many households received remit-tances from family members working abroad, and these wereespecially important in providing support for post-disasterrecovery. A complex range of issues did, however, limit theeffectiveness of community responses. The residentsreceived no support from government agencies. Indeed,most residents viewed local and national governments asunhelpful or even as a hindrance to their efforts.25

Furthermore, although residents were organized in commu-nity-based organizations, none of these were representativeof the communities.

Where there are representative community-basedorganizations, the possibilities of building resilience toclimate change are much greater. In many countries, thereare now national federations of slum and shack dwellers thathave community-based savings groups as their foundation.Although very few of these savings groups have climatechange adaptation programmes, almost everything that theydo contributes to greater resilience and reduces risks. Thisoften includes many measures taken in response to theextreme weather events that they have long had to copewith. It usually includes measures that make their housessafer – either through support for upgrading (e.g. in Orissa,India, Mahila Milan (Women Together) groups developinghomes that can withstand cyclones and rainfall) or throughacquiring new, safer, more secure land sites upon which tobuild.

Most of what these federations are doing is buildingthe resilience of low-income households to almost all climatechange risks. For instance, a savings account can be drawnon, whatever the shock. Yet, the contribution that thesefederations make to climate change resilience needs to beappreciated. To give but one example from the 30 or socountries that have national federations of slum/shackdwellers: in Dar es Salaam, the Tanzania Federation of theUrban Poor has been active in building resilience in low-income urban communities through a process of communityorganization. This began with savings schemes and enumera-tion exercises (which provide maps and details of allhouseholds in informal settlements), and has expanded toinclude identification and purchasing of land for housing.

The practice of saving regularly has both instrumentalbenefits (the ability of savers to access funds when neces-

In practice, thedevelopment ofinfrastructure whichreduces climatechange impacts isoften beyond thecapabilities of eventhe best organizedand most representativecommunity organizations

Effective risk reduction is possibleif household,community andgovernment investments andactions worktogether in a coordinated manner

Almost everythingthat [community-based savingsgroups] docontributes togreater resilienceand reduces risks


sary) and organizational benefits (the relationships of trustbuilt up within small savings groups that allow theirmembers to work on collective solutions to larger problems).Small-scale loans managed by these savings groups andrepaid over short time periods provide much needed capitalfor livelihood activities, or responses to shocks and stresses.The creation of savings organizations also provides the basis

by which individuals and households can come together toidentify and acquire residential land on sites that are less atrisk of flooding. Local initiatives have also built resiliencethrough improving the supply of potable water (reconnectingand managing water kiosks); engaging in capacity-buildingfor hygiene promotion; and implementing innovative small-scale solid waste management strategies.


Box 6.3 Risk reduction by the Homeless People’s Federation of the Philippines

Sources: Reyos, 2009; Dodman et al, 2010a

The Homeless People’s Federation of the Philippines is a national network of 161urban poor community associations, with more than 70,000 individual members. Itrepresents communities and their savings groups from 18 cities and 15 municipali-ties. The federation and its community associations are engaged in a wide range ofinitiatives to secure land tenure, to build or improve homes, and to increaseeconomic opportunity. The federation also works with low-income communitiesresiding in areas at high risk from disasters, assisting in reducing risks, or, whereneeded, in voluntary resettlement; or in community-driven post-disaster recon-struction.

The federation’s responses to disaster events provide relevant insights forcommunity-level responses to climate threats. The principles behind, and processesof, disaster risk reduction and climate change adaptation have many similarities.Both address the hazards that will affect particular locations and individuals, andthey share an acknowledgement of the importance of addressing root causes ofvulnerability.

The federation is engaged in three main activities that build resilience andfacilitate adaptation to climate change:

• First, the interventions of the federation have a strong focus on land andshelter. Unsafe housing that cannot resist extreme weather events, located onland that is at risk of a range of climate-related hazards, is often at the core ofvulnerability for low-income urban residents. The failure of local and nationalgovernments to address this issue is one of the main factors contributing torisk. By working collectively to acquire land and to obtain financing to buildmore resilient structures, federation members have addressed this aspect ofvulnerability.

• Second, collaboration with the state ensures that interventions can take placeat a larger scale. An active and well-organized body of citizens and communityorganizations can provide the impetus for local authorities to support locallybased adaptation strategies. In Iloilo, a coastal city that frequently suffers fromextreme flooding, the federation has been actively involved in the planningprocess for a flood control project, and has been able to encourage particularinterventions that meet the needs of the group’s members.

• Finally, collective savings at the community level act to provide a source offunds that can be used for pre-event preparation and post-event response, aswell as for longer-term support of livelihood activities. More importantly, theprocess of saving builds trust among members of savings groups and enablesthem to make collective responses to immediate threats and to developstrategies for future actions that strengthen livelihoods and build resilience.Strong local organizations can prevent the sense of dependency that oftenresults after disaster events. In Bikol Province, savings groups helped partici-pants to define and realize their own preferred development response to adevastating mudslide generated by Typhoon Reming in November 2006.According to the federation’s regional coordinator, Jocelyn Cantoria, ‘theadoption of the savings programme [has shown that the communities] can be

self reliant and not be dependent on government dole-outs … they haveshown that they can collectively contribute to their own development and tothat of the municipality as well’.

The Homeless People’s Federation has a national programme that includes theorganization and mobilization of low-income communities in high-risk areas. Forthese communities, the federation promotes and supports the scaling-up ofcommunity-led processes for identifying and acting on disaster risk that includessecure tenure, adequate housing, basic services, disaster risk management and,when needed, relocation. Activities range from community visits; consultations;preparation of settlement profiles and enumerations; hands-on training; learningexchanges; temporary/transitional housing construction; land acquisition; participa-tory site and housing design; planning, construction and management; engagementsand advocacy and building learning networks among high-risk or disaster-affectedcommunities. A review of lessons learned from the federation’s experiencehighlighted the following:

• Savings groups within the settlements affected helped to provide immediatesupport for those affected by the disasters.

• Existing community organizations within high-risk settlements can help toprovide immediate relief and foster social cohesion with tools to supportthem taking action to resolve longer-term issues, such as rebuilding or reloca-tion. Representative community organizations are needed to manage difficultissues – such as who gets the temporary accommodation; who gets priorityfor new housing; and how to design the reblocking that accommodates every-one. In communities lacking such organizations, visiting federation leadersencouraged and supported their formation and capacity to act.

• The visits to the disaster sites by teams of community leaders from the feder-ation and community exchanges that support the survivors’ learning onsavings management, organizational development, community surveys andhouse modelling – developing life-size models of houses to see which designand materials produce the best low-cost housing – have proved to be animportant stimulus for the development of community organizations.

• Community profiling and surveys helped to mobilize the people who wereaffected, and also helped them to get organized and to gather data about theresidents and the disaster site needed for responses. It also supported themby showing their capabilities to the local government.

• The importance of being able to obtain land on a suitable well-located site, insituations where relocation is necessary, was highlighted.

• The importance of having regional organizations to support each settlementwhen disasters affect many different settlements was emphasized.

• Supportive local governments and national agencies are important in that theyhelp with much of the above. This is important with respect to getting accessto land and/or obtaining land titles, as well as in the form of high-level politicalsupport to obtain more rapid response from bureaucracies.

In the examples given above from Orissa and Dar esSalaam, the savings groups and their federations not onlyorganize and act, but also seek partnership with, andsupport from, government agencies. This is also the case inthe Philippines, where there are some interesting andhighly relevant examples of community-based responses toextreme weather events that were driven by savings groupsformed by low-income groups and the Homeless People’sFederation of the Philippines, of which they were members(see Box 6.3). The Philippines is regularly affected by earth-quakes, volcanic eruptions, typhoons, storm surges,landslides, floods and droughts. Many low-income urbanresidents groups live in high-risk sites and have poor-quality housing; they also have little or no protectiveinfrastructure and less resources to call on after disasters.Risk levels have probably increased and are likely tocontinue increasing because of climate change. Theresponse of the Homeless People’s Federation is to gethousehold, community and local governments to worktogether, as neither of them have the resources and capaci-ties to reduce risks by themselves.

Although communities are taking action to adapt toclimate change-related risks, such as floods and high temper-atures, they face a number of challenges in this respect. Asnoted earlier, there are limits to what community-basedaction can achieve in urban contexts. Much adaptation (anddisaster risk reduction) needs the installation and mainte-nance (and funding) of infrastructure and services that are ata scale and cost beyond the capacity of individuals orcommunities. However, the limitations in local governmentcapacity – or local government unwillingness to work with

those living in informal settlements – mean that what house-holds and communities in informal settlements do are oftenthe only adaptation responses that are actually implemented.Furthermore, it is mostly low-income households andcommunities who have to rely on community-based actionsand community preparedness because they are located inmore vulnerable sites, their homes are of poorer quality andthey receive less protection from infrastructure or insur-ance. In this sense, middle- and high-income groups facemuch lower levels of risk, and usually have much less needfor community-based action to remedy deficiencies in infra-structure and services.

There are also difficulties in getting the neededcooperation among community residents for collectiveresponses to climate change risks. This is partly related tothe extent to which community organizations comprehen-sively represent the needs and priorities of those most at riskor most vulnerable. In reality, community organizations arenot necessarily accountable to, or fully representative of, alllocal residents and their needs.26 In many contexts andsocieties, women and particular groups within communities(such as racial, ethnic or other minorities) face discrimina-tion from other residents or resident organizations and lackvoice. It is not surprising, then, that it is often difficult to getagreement and commitment from all inhabitants of a settle-ment for community-based actions.

In urban areas in developing countries, an additionalchallenge relates to the need for community-based adapta-tion to focus on using, protecting and enhancing the assetsavailable to the urban poor.27 As such, it includes the use of arange of assets to make livelihoods more resilient so that

The limitations inlocal governmentcapacity – or …unwillingness … –mean that whathouseholds andcommunities ininformal settlementsdo are often the onlyadaptationresponses that areactuallyimplemented

It is often difficult toget agreement andcommitment fromall inhabitants of asettlement forcommunity-basedactions


Areas of Asset-based actionsintervention Household and neighbourhood Municipal/city Regional or national

Protection Household and community-based Work with low-income communities to Government frameworks to support actions to improve housing and support slum and squatter upgrading household, neighbourhood and municipal infrastructure. informed by hazard mapping and action; risk reduction investments and Community-based negotiation for vulnerability analysis. actions that are needed beyond urban safer sites in locations that serve Support increased supply and reduced costs boundaries.low-income households. of safe sites for housing.Community-based measures to build disaster-proof assets (e.g. savings) or protect assets (e.g. insurance).

Pre-disaster Community-based disaster preparedness Early warning systems that reach and National weather systems capable of damage limitation and response plans, including ensuring serve groups most at risk; preparation of providing early warning; support for

that early warning systems reach safe sites with services; organization for community and municipal actions; everyone, measures to protect houses, transport to safe sites; protecting evacuated upstream flood management.safe evacuation sites identified if areas from looting.needed, and provision to help those less able to move quickly.

Immediate Support for immediate household Encourage and support active engagement Funding and institutional support for post-disaster and community responses to reduce of survivors in decisions and responses; community and municipal responses.response risks in affected areas, support the draw on resources, skills and social capital

recovery of assets, and develop and of local communities; rapid restoration implement responses, including of infrastructure and services.cash-based social protection measures; plan and implement repairs.

Rebuilding Support for households and Ensure reconstruction process supports Funding and institutional support for community organizations to get back household and community actions, household, community and municipal to their homes and communities, and including addressing priorities of women, action; address deficiencies in regional plan for rebuilding with greater children and youth; build or rebuild infrastructure.resilience; support for recovering the infrastructure and services to more household and local economy. resilient standards.

Source: adapted from Moser and Satterthwaite, 2008

Table 6.1

Examples of asset-based actions atdifferent levels to buildresilience to extremeweather

they can cope with a range of challenges, some of which canbe predicted and others of which are unforeseen. In thiscontext, community-based adaptation and pro-poor adapta-tion are intrinsically linked. Pro-poor adaptation raisesimportant questions about the types and aims of responses;who bears any costs; who is involved; and who benefits.28 Italso needs to address the range of reasons why the urbanpoor are disproportionately vulnerable to climate change,including their greater exposure to hazards, the lack ofhazard-reducing infrastructure, the lack of state provision forassistance after extreme events, and the lack of legal andfinancial protection.29

Table 6.1 presents an asset-based framework tosupport resilience to extreme weather that includes protec-tion (much of it reducing disaster risk), pre-disaster damagelimitation, immediate post-disaster response, and rebuild-ing.30 An asset-based approach helps to identify the assetvulnerability to climate change of low-income communities,households and individuals, and considers the role of assetsin increasing adaptive capacity. Strengthening, protectingand adapting the assets and capabilities of these groups isnecessary to reduce urban poverty, while making thembetter able to cope with gradual climate change and extremeevents. However, as illustrated in the table, a number ofactions cannot be undertaken by households and communi-ties alone, but need to be addressed at the municipal/city ornational level. Such actions are the focus of the next section.

LOCAL GOVERNMENTRESPONSES TO THEIMPACTS OF CLIMATECHANGEAs noted in the previous section, the main responsibility forimplementing policies to address the impacts of climatechange in cities rests with local governments. Yet, many citygovernments around the world have so far failed to acceptand/or act upon this responsibility, with the result that manyhouseholds and communities have been forced to implementclimate change adaptation measures on their own. As thediscussion above has shown, however, there are significantlimitations as to what community-based adaptation canachieve. A partnership approach – involving households andcommunities, but also the various levels of government andother partners – is the most effective way to implementclimate change adaptation strategies.

In some places, local governments have taken note ofthe damaging impact of particular storms or heavy rainfallthat have highlighted risks that climate change is likely toexacerbate.31 Elsewhere, the perceived vulnerability ofurban economies, populations, assets and infrastructure hasencouraged more local government engagement, includingsome local governments in middle-income countries forwhom an adaptation agenda seems more relevant since itaddresses local concerns and can include co-benefits withdevelopment.32 These responses have varied from an initialconsideration of likely risks and threats to some particular

infrastructural investment and physical interventions, to thedevelopment of plans and strategies.

However, and as noted above, the primary responsi-bility for developing national policies and programmes onclimate change adaptation rests with national governments.National governments are also custodians of the interests ofurban (and rural) residents in international climate changenegotiations, and in the development of internationalfunding sources and institutions, and other forms of supportfor adaptation. Thus, the first part of this section brieflyreviews national frameworks that support climate changeadaptation in urban areas. This is followed by a discussion ofwhat is done at the local level with respect to climate changeadaptation. It describes how a small, but growing, number ofcity governments around the world have begun to recognizethe threats posed by climate change, first in developed andlater in developing countries. It provides examples of citiesin countries that are at various stages of climate changeimpacts assessments, as well as examples of cities that havedeveloped adaptation strategies, before briefly reviewing thelinks between climate change adaptation and disasterpreparedness.

National frameworks that support adaptation in urban areas

Figure 6.1 outlines the required steps in developing nationalclimate change adaptation policies and programmes.Although the Organisation for Economic Co-operation andDevelopment (OECD) report where this figure originallyappeared used the figure to illustrate what was happening atthe national government level, the figure fits well in aconsideration of what city governments are doing and whichof the steps they are taking (and which they are not). Asindicated in the figure, adaptation planning and implementa-tion have to be based on an assessment of historical andpresent climate conditions, projections of climate change, aswell as current and future implications on vulnerability andimpacts. Such assessments are the foundation of adaptationpolicies, which may be understood as the formulation ofintentions to act, on the one side, and adaptation actions, onthe other. The former include identification of adaptationoptions and discussions of how these fit in with other existing policies. The adaptation actions include the estab-lishment of institutional mechanisms to guide and imple-ment adaptation action; the formulation of new adaptationpolicies and modification of existing policies to take adapta-tion into account; and the explicit incorporation ofadaptation measures at the project level. Figure 6.1 alsoillustrates how adaptation actions undertaken now influencethe assessment of future climate change impacts.

The report from which Figure 6.1 is drawn also classi-fied OECD countries in three categories with respect to thecriteria in Figure 6.1. According to this review (undertakenin 2006), 7 OECD countries were classified as being in earlystages of impact assessments; another 27 countries wereundertaking advanced impact assessments, but were slow inthe development of adaptation responses; while only 5OECD countries had advanced impact assessments and were

Community-basedadaptation and pro-poor adaptationare intrinsicallylinked

A partnershipapproach – involvinghouseholds andcommunities, butalso the variouslevels ofgovernment andother partners – isthe most effectiveway to implementclimate changeadaptation strategies

The primary responsibility fordeveloping nationalpolicies andprogrammes onclimate changeadaptation restswith nationalgovernments


moving towards implementing adaptation. This and otherassessments33 show that relatively few national governmentsare moving towards implementing adaptation initiatives. Areview of what governments in developing countries aredoing on adaptation suggested that many are initiating orsponsoring studies of the likely impacts of climate change;but rarely is urban adaptation given much attention.34

Many countries have developed National AdaptationProgrammes of Action (NAPAs)35 and most recognize theneed to strengthen local capacity to plan and act – including changing local building and infrastructure standards andland-use plans. Yet, these NAPAs have rarely engaged theinterest of the larger, more powerful national ministries oragencies, or of city or municipal governments. Many givesurprisingly little attention to urban areas, given the impor-tance of urban economies to national economic success and,for most countries, to the incomes and livelihoods of muchof the population.36

It is also difficult to ensure that NAPAs do not becomejust another policy document that gets little or no action onits recommendations:

Countries are already bombarded with interna-tional obligations, which place considerablestrain on already overloaded institutions withlimited capacity, and which may well lead toduplication of effort and reduction in policycoherence.37

It must also be remembered that NAPAs’ effectivenessdepends on their catalysing and supporting local assessmentand action. It has been suggested that what is needed is city-focused City Adaptation Programmes of Action andlocal-focused Local Adaptation Programmes for Action.38 Asstressed throughout this chapter, risks and vulnerabilities forall aspects of climate change in urban areas are greatlyshaped by local contexts and influenced by what localgovernments do or do not do. Effective adaptation needs tobe based on a good understanding of the local context andstrong local adaptive capacity. It needs City AdaptationProgrammes of Action and, very often, smaller-scale LocalAdaptation Programmes for Action that incorporate commu-nity-based adaptation – especially for the settlements orareas most at risk. Much more needs to be done in terms of

‘mainstreaming’ adaptation to climate change withinnational policy-making processes39 and putting in place thesystems and structures that encourage and support city-driven and locally driven adaptation. Perhaps more to thepoint, unless adaptation is seen by national and city govern-ments in developing countries to be complementary todevelopment agendas, it will not get considered.

Local government responses in developing countries

As noted above, there are not many examples of cities indeveloping countries that have initiated climate changeadaptation policies. The bulk of the examples that exist arecities that have started the process outlined in Figure 6.1 byassessing the risks posed by future climate change. Somesuch examples are outlined below, followed by a discussionof the experiences of cities that have taken this assessmentone step further by showing a concrete intention to actthrough the development of adaptation strategies.

n Assessing climate change risks and the scaleof the adaptation deficit

Generally, the first evidence of an interest by city or munici-pal government in climate change is an interest in assessingthe scale and nature of likely risks. Yet, this assessment is noteasily done for most developing country cities because of thelack of basic data on environmental hazards and risks (oreven of an accurate and detailed map with all settlements onit). It is thus important to note (again) that most climatechange-related risks (at least in the next few decades) are anexacerbation of risks already present, which are the result ofthe inadequacies in local governments’ capacities or willing-ness to manage and govern urban areas. Thus, there is alarge deficit in the basic infrastructure and services neededto address not only risks related to extreme weather andwater constraints, but also ‘everyday’ risks. A city wheremuch of the population live in areas that are frequentlysubjected to floods – because these areas lack storm andsurface drains (and often because areas at risk of flooding areamong the only areas where low-income groups can buy,build or rent accommodation) – is a city that is more at riskfrom more frequent or intense rainstorms. The deficits inbasic infrastructure and services are not the result of climatechange, and funding agencies that support climate changeadaptation may judge these (often vast) deficits in infrastruc-ture and services as being outside the scope of climatechange adaptation. Box 6.4 gives some examples of the scaleand nature of these deficits.

Three examples are provided below of cities for whichthis first step (i.e. of mapping the tasks at hand) has beentaken – namely, Georgetown (Guyana), Bangkok (Thailand)and Dhaka (Bangladesh). These three examples show howclimate change risks come to be identified and discussed,and highlight the initial thinking of what measures areneeded to address these. Nonetheless, there is still the needto incorporate measures to address these risks into cityplans, land-use management, infrastructure investments,service provision, and building and planning codes, and

Relatively fewnationalgovernments aremoving towardsimplementingadaptation initiatives

Funding agenciesthat support climatechange adaptationmay judge …deficits ininfrastructure andservices as beingoutside the scope ofclimate changeadaptation


Figure 6.1

The main stages of city-based climatechange adaptation

Source: based on Gagnon-Lebrun and Agrawala, 2006,Figure 6

Climate change and impact assessments

Current conditionsin light of historic

climate trends

Climate change scenarios and their

implications

Impacts and risks/vulnerabilityassessments

Intention to act

Identifyingadaptation

options

Considering existing policies

synergistic with adaptation

Establish institutionalmechanisms to

support local action

Formulate policies or modify existing policies (e.g. infrastructure and

coastal zone management)

Explicitincorporationof adaptationin projects

Adaptation actions

Adaptation

there is much less evidence of this taking place. The sectionof the city government that prepares (or commissions) theseinitial assessments may have little political support withinthe city government or may be unable to convince the morepowerful sectoral agencies within the government to change their plans and investments in response to the risks identified.40 Inevitably, any forward-looking risk-reducinginvestment programme that needs serious funding will facecompetition from other sectors.

In Guyana,41 the coastal zone that includesGeorgetown holds 90 per cent of the country’s populationand much of the economy. Its highest point is only 1.5mabove sea level, with much residential land, including thecapital Georgetown, below the sea level at high tide. Largesections of Georgetown’s population experience regularfloods.42 Adaptation planning for the densely settled areasaround Georgetown has been conducted by an internationalmanagement consultancy firm, with the intention of identi-fying and analysing adaptation investment options. Riskswere assessed through analysing major climate hazards,identifying the major assets at risk and assessing the vulnera-bility of these. The main climate hazard facing Guyana, andparticularly the densely populated areas near Georgetown, isflooding caused by heavy rains. A variety of scenarios havebeen developed to estimate the potential for financial lossesin the public, agricultural, industrial and commercial, andresidential sectors in 2030.

In Georgetown, there is also evidence of the secondstage of city-based adaptation – identifying adaptationoptions and considering existing policies that are synergisticwith adaptation (see Figure 6.1). Key adaptation interven-tions that were identified as being economically attractiveincluded the expansion of early warning infrastructure; theimprovement of building codes for new construction; themaintenance of drainage systems; and the upgrading ofdrainage systems. In each of these cases, there was a cost-benefit ratio of less than 1.0, implying that such measureswere economically viable. Several adaptation measures wereassessed quantitatively. These include:

• Infrastructure measures: repairing and maintaining thesea wall.

• Health measures: flood-proofing health clinics, sanita-tion and water, emergency response system.

• Financial measures: cash reserve, contingent capital,strengthening the primary insurance market.

Of these, repairing and maintaining the sea wall, developingan emergency response system and providing contingentcapital were seen as generating the most important benefits.Sections of the sea wall are in disrepair and upgrades are needed to protect against coastal flooding; emergencyresponse capabilities currently do not exist; and risk financing can provide money in the case of a crisis event.

Any forward-lookingrisk-reducing investmentprogramme thatneeds seriousfunding will facecompetition fromother sectors


Box 6.4 The scale of adaptation deficit in selected cities

Dar es Salaam.a This is the largest city in Tanzania, with more than 3.3 million inhabitants in 2010, compared to less than 0.2 million in 1960.b

As a coastal city, it faces climate change-related risks from sea-level rise and coastal erosion, flooding, drought and water scarcity, and thedisruption of hydroelectricity generation. These issues are much exacerbated by the mismatch between the growth of the city (and the cityeconomy) and the capacity of the local governments within Dar es Salaam. Some 70 per cent of the population live in informal and/or illegalsettlements and most lack adequate provision of basic infrastructure and services, including piped water supplies and provision for sanitation,drainage and solid waste collection. Low-income residents in the city are already coping with a range of climate-related challenges, particularlyrelated to seasonal flooding. Uncollected garbage blocks both natural and artificial drainage channels, which causes flooding after heavyrainfall.

Dhaka.c Bangladesh is frequently identified as one of the countries most at risk from the effects of climate change. Its large and rapidlygrowing capital Dhaka is particularly at risk; a population that grew from 0.5 million in 1960 to 14.6 million in 2010b has long outstripped theexpansion of infrastructure, including flood protection. This is a city already very vulnerable to flooding, especially during the monsoon season– as shown by major floods in 1954, 1955, 1970, 1980, 1987, 1988, 1998 and 2004. The 1988, 1998 and 2004 floods were particularly severe,with very large economic losses. These were mainly caused by the spillover from surrounding rivers. The city has a very large deficit in termsof the proportion of the population living in slum areas, with overcrowded, poor-quality housing that lack piped water, sewers and drains.

Lagos.d The location of Lagos (Nigeria) on a narrow lowland coastal stretch bordering the Atlantic Ocean puts it at risk from sea-level riseand storm surges; much of the land in and around Lagos is less than 2m above sea level. Yet, it is the lack of attention by state and localgovernments to the needed storm and surface drains and other infrastructure, and also to land-use management, that has created most of therisks from flooding. The city has expanded rapidly – from less than 0.8 million in 1960 to 10.5 million in 2010b – and much of the populationgrowth has been housed in informal settlements in marshy areas or near (or even over) the lagoons. Much of the city lacks the infrastructureneeded to limit floods; a high proportion of residents lack not only storm drains, but piped water, sanitation, electricity, all-weather roads andsolid waste collection. To this is added the lack of maintenance of storm drains (especially de-silting before the rainy season), the drains andgutters blocked with solid wastes (because of no household solid waste collection service) and the unauthorized buildings that encroach ondrains. The expansion of low-income settlements in areas at high risk of flooding (many on stilts) is largely because there are no safer sitesavailable that they can afford.

Sources: a draws on Dodman et al, 2010b; b UN, 2010; c draws on Alam and Rabbani, 2007; Ayers and Huq, 2009; Roy, 2009; d draws on Adelekan, 2010; Iwugo et al, 2003; Adeyinka and Taiwo, 2006

Additionally, these are relatively low-cost interventions.Thus, some substantial adaptation benefits can be achievedfor relatively low costs. This approach has great value inidentifying the most cost-effective adaptation responses atthe city level, and can help local and national officials toidentify the most appropriate interventions. However, itwould probably be best used in association with detailedsocial analysis to ensure that adaptation activities meethuman development needs as well as being cost effectivefrom a financial perspective.

The Metropolitan Administration of Bangkok(Thailand) has also begun mapping the climate change-relatedrisks that the city will face; based on this, it is proposing avariety of policy-based, infrastructural and environmentalresponses (see Table 6.2).43 Bangkok is vulnerable to a rangeof climate threats as a result of its location on a low-lyingplain affected by subsidence, close to the sea and subjectedto regular monsoon rains. A risk management approach isassessing the potential consequences of climate change andidentifying appropriate responses. An initial risk assessment –which highlighted flooding, storm surges, drought and risksto the security of the water supply – has been conducted, andthese risks will be analysed more extensively to informadaptation interventions. More overarching adaptationmeasures will include capacity-building activities, improvedcommunication between scientists and city officials, encour-aging the development of climate change risk assessments atthe local level, and raising awareness of climate change inhomes and communities.

Box 6.4 highlights the climate change-related risksfaced by Dhaka (Bangladesh). This is a city with a relatively

long history of environmental and climate change aware-ness, policy and action. It was the first of the least developedcountries to complete its National Adaptation Programme ofAction (NAPA), and there is a significant effort by thenational government to integrate climate change withinsectoral plans and policies. The Dhaka Metropolitan Develop-ment Plan is intended to meet many climate adaptationneeds. For example, a strategic approach to planning couldhelp to enhance response capacity; increased public partici-pation in the planning process could raise public awarenessof climate-related threats; and the implementation of sitesand services schemes could reduce the vulnerability of theurban poor and enhance their resilience.44

At the city level, large-scale flood protection measuresare an essential component of an adaptation response. Since1989, an extensive system of embankments has beenconstructed, and further investments of this type arecurrently planned.45 Canals and drainage systems arecurrently being renovated, and the banning of polythenebags has helped to reduce the clogging of the city’s drainagesystem.46

n Moving from risk assessments to adaptation strategies47

Within Africa, South Africa is unusual in having discussionswithin several city governments on climate change adapta-tion and thus moving beyond risk assessments to discusswhat should be done to address the risks. A number of SouthAfrican cities have thus developed plans for adapting toclimate change. These have been made possible through thestrong support of a range of stakeholders, including universi-

Within Africa, SouthAfrica is unusual inhaving discussionswithin several citygovernments onclimate changeadaptation …moving beyond riskassessments todiscuss what shouldbe done to addressthe risks


Climate change impact Adaptation measuresCommunity infrastructure Business and commercial Residential health and and operations general population

General long-term rising • Urban design • Actions to reduce urban heat island, • Better insulationtemperatures of 3°C–5°C • Tree-planting including building design and green • Design for efficient cooling

• Water conservation spaces • Pest and insect controls• Insect and pest controls • Water conservation

Ground and surface water • Water-use restrictions • Water efficiency and conservation • Water efficiency and conservation quantity and quality • Optimize reservoir releases programmes programmes

• Expand storage capacity • Water pricing• Greater regulation of surface and • Irrigation practices

groundwater withdrawalsSea-level rise (especially in • Land-use planning • Coastal protection • Land-use planningBang Khuntien District) • Construction or improvement of • Phased retreat • Ecosystem protection

levees and dykes • Modifications to operation of port• Creation of water reservoirs

Extreme weather-related • Emergency preparedness plans • Emergency preparedness plans • Emergency preparedness plansevents (windstorms, • Construction or improvement of • Flood-proofing of buildings • Flood-proofing of homesprolonged rain, river levees and dykes • Elevation of buildings • Publicly sponsored flood insuranceflooding, drought) • Elevation of buildings • Behavioural changes for disaster

• Land-use planning preparation (e.g. emergency • Increase resilience of electricity supplies)

network• Improve emergency communications

Increased frequency and • Increased size of storm drains, etc. • Increase water-absorbing capacity of • Storm sewer protection and intensity of short-duration • Increased water-absorbing capacity large paved areas maintenanceheavy rains of urban landscape • Landscape design to reduce

rapid runoffIncreased frequency and • Use of air conditioners • Use of air conditioners • Use of air conditionersintensity of heat waves, • Heat contingency planning • Rescheduling protection when • Public education on behavioural droughts and smog episodes • Reduction of urban traffic necessary responses

• Planting of trees

Source: based on Bangkok Metropolitan Administration, 2009, Table 6.1

Table 6.2

Adaptation measuresfor Bangkok, Thailand

ties and local authorities. The transition to democracy in1994 generated new local government structures whichincluded a specific mandate and focus on environmentalmanagement, alongside a significantly revised developmentagenda. This section reviews the experience with developingsuch climate change adaptation plans in Durban and CapeTown.

Durban has one of the most interesting experiencesin developing climate change adaptation plans and strategiesbecause of the innovations that it has demonstrated, andbecause of the documentation of the internal processes bywhich it advanced and by which it was constrained.48

Durban is South Africa’s largest port and city on the eastcoast of Africa, with a population of 2.9 million people in2010.49 The local government structure responsible formanaging the city is known as eThekwini Municipality.During the 1990s, the municipality had become a leader inthe field of local-level environmental management50 and hadalso initiated some work on mitigation. The city’s planningfor adaptation built on these experiences.

Between 2004 and 2006, eThekwini Municipalitydeveloped a locally rooted climate change adaptation strat-egy.51 This is encapsulated in the Headline Climate ChangeAdaptation Strategy, which addresses both direct andindirect issues in links between climate change and humanhealth, water and sanitation, coastal zone management,biodiversity, infrastructure and electricity supplies, trans-portation, food security and agriculture, and disaster riskreduction. Initially, the development of this high-level strat-egy did not result in any additional innovation or movementfrom the ‘business-as-usual’ scenario in terms of municipalfunctioning and the plans and investments of the larger andmore powerful sectors. Climate change risks were seen byother sectors in government as too generic and the risks itoutlined too distant; there was also an assumption by manythat these were the responsibility of the city’s environmentaldepartment. There were also other factors drawing attentionaway from it, such as high existing workloads and urgentdevelopment challenges and pressures. The municipality’sdisaster management unit was an obvious ally – but it lackedcapacity and was seen by the municipality as a responsiverelief agency, and thus not an influence on infrastructureinvestments or city planning.

As a result, and in order to engage municipal linefunctions more effectively in targeted and prioritized climatechange adaptation, the adaptation planning process wasdeepened through the development of more detailedsectoral municipal adaptation plans. At this stage, particularattention was paid to three high-risk sectors (water, healthand disaster management) since these form a natural clusterof integrated functions, thereby offering opportunities forcross-sectoral integration and coordination. This sectoralapproach has proved to be more successful in facilitatingmeaningful action, and in time will be rolled out across allrelevant municipal sectors. It is through the identification ofissues that are relevant to particular sectors within govern-ment that their engagement is ensured. Also important forthis is that they see climate change adaptation as directlylinked to development (and their development and invest-

ment plans). As a staff member from eThekwiniMunicipality’s Environmental Planning and ClimateProtection Department has noted:

... the more sectoralised approach to adaptationplanning now being adopted in Durban has hadthe effect of encouraging a greater interactionamongst the line functions than occurredduring the development of the cross-sectoral[Headline Climate Change AdaptationStrategy]. This can be linked to the clearerdefinition of tasks and objectives that hasemerged from the more detailed understandingof sectoral needs and limitations.52

While climate change has emerged as a significant issue inmunicipal plans in Durban, and staff and funds have beenallocated to climate change issues, the emergence of climatechange advocates among local politicians and high-rankingcivil servants has been a slower process. However, this ischanging, as the mayor and other key officials become moreactively engaged in the climate change debate. A process ofcommunity-level adaptation planning has now also beenfacilitated in order to complement and extend the municipal-level interventions. Specific adaptation interventions haveincluded:

• increasing the water-absorbing capacity of the urbanlandscape;

• improving urban drainage and storm-sewer design;• increasing natural shoreline stabilization measures;• utilizing storm water retention/detention ponds and

constructed wetlands;• land-use planning to avoid locating structures in risky

areas;• working with industry to reduce water demand;• increasing food security;• using environmental management as the basis for creat-

ing ‘green jobs’.

The progress in Durban depended on the mobilization ofpolitical support for adaptation, and the presence of engagedand motivated stakeholders. However, moving from strategicplans to specific projects will require additional stages ofplanning and dedicated sources of financing.53 For thispurpose, four institutional markers may be identified forassessing progress in any city towards climate change adapta-tion:54

1 the emergence of an identifiable political/administrativechampion(s) for climate change issues;

2 the appearance of climate change as a significant issuein mainstream municipal plans and in stakeholderdiscussions;

3 the allocation of dedicated resources (human and finan-cial) to climate change issues;

4 incorporating climate change considerations withinpolitical and administrative decision-making.

Climate change riskswere seen by othersectors in government as toogeneric and the risks it outlined toodistant; there wasalso an assumptionby many that thesewere the responsibility of thecity’s environmentaldepartment

Moving from strategic plans tospecific projects willrequire additionalstages of planningand dedicatedsources of financing


However, and perhaps obviously, the integration of climateprotection considerations within political and administrativedecision-making is unlikely to be a smooth process. Anythingthat affects budget lines and Durban’s current desired devel-opment path will be contested.55

In Cape Town (South Africa), a framework has beenproposed for the development of a municipal adaptation planfor climate change (see Figure 6.2) in a document commis-sioned by the city government. The various steps involved inthis process are complemented by two cross-cuttingprocesses: stakeholder engagement is playing an importantrole in identifying vulnerable sectors and potential initia-tives, and also brings politicians and decisions-makers onboard; and an assessment of adaptive capacity (the ability ofa system to respond to the impacts of climate change). Themunicipal adaptation plan should be the final output of thisprocess; but a variety of intermediate documents will beproduced, including vulnerability maps and assessments tohighlight ‘hotspots’ where social and climate risk interact.

However, in Cape Town, as in all cities, it will be diffi-cult to get the attention of senior politicians and civilservants with regard to climate change adaptation. Forinstance, in the summary of Cape Town’s integrated develop-ment plan,56 no mention is made of climate changeadaptation. For Cape Town and many other cities, the firstreal engagement with climate change adaptation is likely tobe through responses to disaster risk. In May 2010, the Cityof Cape Town’s website described the long-range weatherforecasts that indicated the possibility of above normalrainfall for the coming winter months and the measures thatwere being taken to cope with them by various city depart-ments.57

Local government responses in developed countries

Adaptation responses in cities in developed countries aregenerally much easier to formulate, implement and fund,although not necessarily easier in terms of getting the

needed political support. Yet, such cities do not have verylarge deficits in infrastructure; most or all of their populationlive in buildings that meet building standards and are servedby piped water supplies, sewers, drains and solid wastecollection. These cities also have a range of regulations andcontrols that (when implemented) reduce risks, as well asmeasures and institutional arrangements that ensure rapidand effective response to disasters, thus limiting theirimpact when they happen, especially for those who are mostat risk.

While the scale of risks and of the populationsexposed to them are much smaller and the local capacities toaddress these much larger, this does not mean that adapta-tion is necessarily given the priority that it deserves. Thereare many relatively wealthy cities that need major upgradesin their infrastructure that should take account of likelyclimate change impacts. In general, most cities in developedcountries need to expand their capacity to anticipate andmanage extreme weather events. There are also cities thatare on sites that are or were relatively safe without climatechange, but that now face new levels of risk. For instance,many coastal settlements, whether villages, towns or cities,face increased risks from sea-level rise. Climate change islikely to bring more extreme and frequent heat waves tomost regions, with higher risks in large cities or particular‘heat islands’ within such cities. Many cities will faceconstraints on freshwater supplies. However, althoughadaptation plans for urban centres in developed countrieswill have many characteristics in common, the particular mixof needed measures will be very specific to each urbancentre. For instance, and as discussed below, the measuresto adapt to sea-level rise in the adaptation plans of London(UK), Melbourne (Australia) and Rotterdam (TheNetherlands) take different forms, and their integrationwithin other measures is specific to each city.

There are also many cities in developed countrieswhere climate change risk, to their governments, seems adistant threat as they are struggling with economic decline.In developed countries, there have been major spatial shiftsin where economic growth and new investment concentrate,which have left many cities that were formerly centres ofindustry and economic success in decline. In such cities, it isdifficult to get much attention to climate change adaptation.

As with earlier discussions of cities in developingcountries, the first step is to get a sense of what new orincreased risks climate change will bring and what impactsthese will or may bring. The examples discussed below –from London, Melbourne and Rotterdam – illustrate this firststep.58 The next step after this is the intention to act (seeFigure 6.1) – seen in the identification of adaptation options,including all the sector-specific actions needed for this or tosupport this; this, too, can be seen in these three cities.

The Greater London Authority has developed aclimate change adaptation strategy that provides the basis foradaptation actions. As one of the world’s wealthiest cities,London has far more abundant financial and technicalresources than most other cities.59 Yet, it faces particularclimate risks as a result of its location (on the River Thames),the age of much of the city’s infrastructure, and the dense

There are manyrelatively wealthycities that needmajor upgrades intheir infrastructurethat should takeaccount of likelyclimate changeimpacts


Figure 6.2

Process for developinga municipal adaptationplan in Cape Town,South Africa

Source: Mukheibir andZiervogel, 2007

Assessment of vulnerabilityto socio-economic stresses

Assessment of vulnerabilityto climate change impacts

Local economic development strategies;integrated development plans;

integrated municipal environment plans

National climate change strategy;local climate change assessments

Overlay to identifyvulnerable areas

Develop adaptation optionsand actions

Prioritizeactions

Municipal adaptationplan

concentration of administrative, commercial and financialactivities that are essential to national – and, indeed, global –finance. The adaptation strategy identifies responses to threekey climate risks: floods, drought and overheating (see Box6.5). This strategy relies on the contributions of a range ofagencies, operating at the scale of the urban area of Londonas well as at the national level.

The Greater London Authority has also recognizedthat the provision of ecosystem services – which may help inthe conservation of biodiversity, reduction of pollution orimprovement in the aesthetic value of surroundings – canalso generate benefits in responding to climate change (seeTable 6.3). There are strong co-benefits for adaptation(reduced flood risk and offsetting of urban heat islands),mitigation (reduced energy demand, support biodiversity)and development (reduced noise and air pollution, increasedprovision for recreation/leisure).

The adaptation strategy of the City of Melbourne(Australia) identifies four main climate risks: reduced rainfalland drought; extreme heat wave; intense rainfall andwindstorm; and sea-level rise (see Table 6.4).60 It also identi-fies seven urban systems where adaptation actions are need-ed: water; transport and mobility; buildings and property;social, health and community; business and industry; energyand communications; and emergency services. The risk

management process that was used to analyse these risksincluded a stage of evaluating risks and deciding whetherthese are acceptable or not. If the risks are deemed to beunacceptable, then they are treated through a process ofadaptation. Throughout, the process is monitored andreviewed, and is linked with communication and consulta-tion. The proposed adaptation measures are intended toreduce the likelihood or consequence of a particular risk orto increase the level of control over it, thereby making ittolerable. These have also been sub-graded to identifywhether they fall into the categories of ‘control critical’,require ‘active management’, require ‘periodic monitoring’or are of ‘no major concern’. The risks, key themes and keyactions are summarized in Table 6.4.

The Greater LondonAuthority has …recognized that the provision ofecosystem services… can also generate benefits in responding toclimate change


Table 6.3

Ecosystem servicesprovided by greenspaces and street trees,London, UK

Box 6.5 Key risks identified by the climate change adaptation strategy of London, UK

The climate change adaptation strategy of London identifies responses to three key climate risks: floods, drought and overheating.The first risk, from flooding, is linked to sea-level rise, increased tidal surges up the River Thames (that runs through London), and

wetter winters with more frequent and intense heavy rainfall (leading to increases in peak river flows of between 20 and 40 per cent). Aseries of ‘decision pathways’ have been developed by the UK Environment Agency (a national governmental body) to respond to this. TheThames Barrier, constructed between 1974 and 1982, is a key part of this strategy – along with 298km of floodwalls, 35 major gates and over400 minor gates. Although this was not designed with climate change in mind, it is a key part of London’s protection against flooding and it hasbeen used far more frequently since 1990. The most recent assessments suggest that in all but the most extreme scenarios, the ThamesBarrier will continue to protect London from flooding, although towards the end of the 21st century it may become necessary to use greenspaces adjacent to the River Thames to store floodwater.

A city-wide water strategy seeks to reduce the effect of the second risk – that is, from water shortages – which are expected tobecome more frequent as climate change accentuates the seasonality of rainfall. Reducing demand for water will increase the length of timerequired until drought measures are required – and will also save money and reduce carbon dioxide emissions. The water strategy proposesthe following four steps for balancing the supply and demand of water:

1 Lose less: reduce the loss of water through better leakage management.2 Use less: improve the efficiency of water use in residential and commercial developments.3 Reclaim more: use reclaimed water for non-potable uses.4 Develop new resources: adopt new resource options that have the least environmental impact.

The third risk is from overheating (i.e. when temperatures rise to a point where they affect health and comfort). Overheating also increasesdemand for energy-intensive cooling (which may lead to power shortages and contribute to increased GHG emissions), a rise in demand forwater (increasing pressure on limited water resources) and damage to temperature-sensitive infrastructure. Four courses of action are beingused to reduce risks:

1 urban greening to reduce the intensification of temperatures by the urban heat island;2 designing new and adapting existing buildings and infrastructure to minimize the need for cooling;3 ensuring that low-carbon energy-efficient measures are used where active cooling is required; and4 helping urban residents to adapt their behaviour and lifestyles to higher temperatures (a key component of this is ensuring that ‘vulnera-

ble’ people are identified and provided with suitable social and medical assistance).

Source: Nickson, 2010

Green Street Wetlands River Woodlands Grasslandsroofs/walls trees corridors

Reduce flood risk 44 4 444 444 44 44

Offset urban heat island 44 44 44 44 444 4

Reduce energy demand 44 44 4

Reduce noise/air pollution 44 44

Support biodiversity 44 4 444 444 444 444

Recreation/leisure 4 4 44 444 444

Source: GLA, 2010, Table 7.1

Two ‘high value’ (or cost-effective) adaptationmeasures have been identified that have the potential toprovide benefits across many risks:

1 storm water harvesting, which can assist in reducing theimpact of flash-flooding events through storing excessstorm water while simultaneously storing water for usein times of drought; and

2 passive cooling, which can reduce the heat-island effectby reducing temperatures both inside buildings and atstreet level, therefore reducing overall exposure to theeffects of heat waves.

This concept of ‘high value’ adaptation can provide a usefultool for adaptation planning, as it indicates the interventionsthat can have the greatest impact. This is an importantconsideration, particularly in a context of resource scarcity.

Perhaps not surprisingly, many cities in TheNetherlands are considering climate change adaptationmeasures. The Netherlands has centuries of experience inresponding to the challenges faced by being low-lying andcoastal. The City of Rotterdam – as a coastal city and one ofEurope’s largest ports – is particularly aware of thesechallenges and is aiming to be climate change proof by2025.61 The main threat to the city (and the main focus ofadaptation measures) is from coastal flooding. Investment inadaptation is necessary to safeguard the health and securityof the population, to prevent damage caused by climatechange from being unmanageable, to increase the return oninvestments in the use of public spaces and infrastructure,and to ensure that solutions are innovative and attractive.Responses to climate change in Rotterdam address three keythemes:

1 Knowledge. Knowledge for climate adaptation is beinggenerated through cooperation with a range of relevant

parties, including water and hydraulic engineering insti-tutes, universities, businesses, water boards, housingcorporations and developers. New research is beingconducted into issues of flooding and heat stress, andknowledge is being exchanged with other port cities,both within and outside The Netherlands.

2 Action. This involves the implementation of projectsdesigned to prevent flooding or to reduce its effects.This includes raising dykes, excavating areas to containextra water, and flood-proofing buildings in areas thatare likely to be flooded. In addition, a variety of inter-ventions will be made to ease heat stress in the city –for example, by providing additional shade and cooling.

3 Marketing. The City of Rotterdam seeks to be at theforefront of adapting to climate change, and will createa distinct profile for itself as a positive example of aclimate-adaptive city in a delta. This is important forrelationships with urban residents, major stakeholders(including government agencies and universities) andother cities around the world.

The links between adaptation and disaster preparedness62

The 1990s brought a shift in the way that disasters and theircauses are understood, with much more attention being paidto the links between development and disasters.63 In LatinAmerica, many city governments began to explore this andimplement disaster risk reduction measures. This wasspurred by the numerous major disasters in the region andsupported by decentralization processes and state reforms inmany countries.64 Several countries enacted new legislationthat transformed emergency response agencies into nationalrisk reduction systems.65 Some city governments incorpo-rated disaster risk reduction within development as theychanged or adjusted regulatory frameworks, upgraded infra-

The 1990s brought ashift in the way thatdisasters and theircauses are under-stood, with muchmore attentionbeing paid to thelinks between development anddisasters


Risk Key themes Examples of specific actions

Drought and reduced rainfall • Maximize water-use efficiency • Save water through demand management strategies and • Diversify water supply behavioural change• Maximize water harvesting • Structural modifications to treat and/or harvest alternative water • Improve waterway and bay health supplies

• Increase installations of rainwater tanks for toilet flushing• Investigate the use of artificial turf on sports fields

Intense rainfall and wind event • Better drainage and storm water capture • Drainage improvements at flash flood points on transport system• Early public warning system • Continued upgrading of storm water infrastructure• Integrated emergency services • Communications programmes to build capacity for dealing with • Better public knowledge and safe behaviour transport delays in extreme events• Minimize debris potential• Increased infrastructure standards

Heat wave and bushfire • Cooler surroundings, inside and out, • Develop and implement heat wave response planthrough improved infrastructure • Identification and care of high-risk populations

• Better public knowledge and safe behaviour • Implement changes to urban form to reduce heat-island effect• Heat-wave early warning system

Sea-level rise • Future-proof planning for sea-level rise • Modelling of flood risk and infrastructure impacts to sea-level rise• Better protection for existing low-lying • Development of suitable planning guidelines to reflect findings

developments of modelling• Better flood control through revised • More extensive storm water capture and reuse

drainage planning • Alteration of at-risk residential buildings to facilitate entrance and exit • Measures to improve resilience to exposed during significant floods

infrastructure

Source: City of Melbourne, 2009

Table 6.4

Key risks and adaptation strategies inMelbourne, Australia

structure and housing in at-risk informal settlements, andimproved urban land-use management with associatedzoning and building codes.

This shift by local governments to disaster risk reduc-tion has been driven by different factors. In some countries,it is driven by stronger local democracies (e.g. a shift toelected mayors and city councils) and decentralization (whencity governments have a stronger financial base). Sometimesthe trigger was a particular disaster event, such as the devas-tation brought by Hurricane Mitch in Central America (in1998). Or it was a sequence of events, such as the Popayánearthquake (1983), the Armero mudslide (1985) and otherdisasters in Colombia. These events encouraged countries,and within these, city and municipal governments, to lookmore closely at the scale and nature of disaster risk andconsider what investments and measures could be put inplace to reduce disaster risks. Innovations here include thoseundertaken by specific local governments, but, as impor-tantly, also those that involve cooperation and coordinatedaction among groups or associations of local governments. Inseveral countries, there are also national systems to supportlocal authorities and other stakeholders in disaster riskreduction.

These have relevance for climate change adaptationbecause many are reducing risk levels or exposure to risk forthe extreme weather events that climate change is, or islikely, to make more intense, frequent or unpredictable.However, they also have relevance beyond this in that manymeasures to reduce disaster risk build resilience to a rangeof hazards. Also, strengthening the capacity to respondrapidly and effectively to disasters and to work with thoseaffected to rebuild their lives, homes and livelihoods willserve all forms of disaster response, whether or not climatechange had a role in the disaster.

By 2007 when the IPCC published its Fourth Assess-ment Report, adaptation to climate change was alreadytaking place in some cities, although these were mostlydriven by climate variability. Indeed, societies have a longrecord of adapting both agriculture and settlements to theimpacts of weather and climate through a range of practicesthat include diversification, water management, disaster riskmanagement and insurance.66 Yet, climate change poses anew set of risks that may be substantially different fromthose experienced in the past, and the challenge for adapta-tion is to ensure that both development needs and the needsimposed by a changing climate (and their link to disasterrisk) are met simultaneously.

TOWARDS EFFECTIVE CITY-BASED CLIMATE CHANGEADAPTATION STRATEGIESWhat can be seen from the examples above are the begin-nings of city-based adaptation strategies in some cities.These are what might be called the early adapters as well asthe early adopters.67 Getting a more widespread attention bycity and municipal governments to climate change adapta-tion will need clearer and more detailed risk assessments

and a better understanding of how adaptation measures canserve and be integrated within development and disaster riskreduction. It also depends on whether local governmentshave the knowledge, capacity and willingness to act.

The experiences discussed above indicate that thereis an obvious interest in reviewing adaptation responses topotential climate change impacts in different sectors – forinstance, in potential damage to infrastructure, to cityeconomies and to public health – and to specific groups thatare more vulnerable. There is also an interest in how adapta-tion responds to the potential social and economic impactsof climate change upon individuals and households, includ-ing those relating to displacement and forced migration (andpossibly to security). In each of these, there are issues ofwhose needs are served (and whose are not) by adaptationresponses, especially in relation to income level, gender andage. Thus, a whole series of questions might be raised toassess the effectiveness of adaptation policies and practices,including, inter alia:

• Do adaptation measures focus on protecting or servingwealthier groups and districts?

• Are those living in informal settlements included and, ifso, does this include all informal settlements or onlythose ‘recognized’ by the government or those who aremore easily accessed?

• Do the particular risks and vulnerabilities women facebecause of their household, childcare and livelihoodresponsibilities, or the discrimination they face ingetting access to services and finance that can supportadaptation, get considered?

• Is the main response in adapting infrastructure toprotect what are seen as the most economically impor-tant city assets, or to protect city populations withparticular attention to those most at risk?

As yet, too few cities have developed coherent adaptationstrategies and even fewer have strategies that have begun tohave a real influence on public investments and to getneeded changes in building and infrastructure standardsand land-use management. Most of the literature on climatechange adaptation and cities is focusing on what should bedone, not on what is being done (because too little is beingdone). For instance, some city adaptation strategies arejustified, in part, by initial figures on the economic assets atrisk or by the damage done by extreme weather in thepast.68 In most developed countries and some othercountries, revisions to building and infrastructure standardsthat increase safety margins for likely climate changeimpacts are being considered. Public health responses toheat waves are being rethought, especially after the limita-tions revealed by the heat wave in Europe in 2003 – andsome cities where heat waves have long been present havestrengthened their capacity to reach and serve many ofthose most at risk. Many local governments have takenmeasures to manage freshwater resources better because ofsupply constraints; in many places, these often serve as thefirst steps for addressing additional water constraintsbrought by climate change.

By 2007 … adaptation toclimate change wasalready taking placein some cities,although these weremostly driven byclimate variability

Climate changeposes a new set ofrisks … and thechallenge for adaptation is toensure that bothdevelopment needsand the needsimposed by a changing climate …are met simultaneously

Too few cities havedeveloped coherentadaptation strategiesand even fewer havestrategies that havebegun to have a realinfluence on publicinvestments


There are also issues regarding the social impacts ofadaptation measures. For the many cities that need majorinvestments in storm and surface drainage systems, theirdesign and construction have the potential to displace infor-mal settlements – especially those alongside existing drainsand rivers – although there are good examples of this beingavoided as drainage capacity is increased.69 Measures to bettermanage water reservoirs and watersheds might include thedisplacement of informal settlements – although there areexamples showing how this can be avoided.70 New controlson coastal development to reduce risks from sea-level riseand storms can threaten existing settlements – as they didafter the Indian Ocean Tsunami in 2004, although here, too,there are examples of alternative practices that have madecoastal settlements more resilient rather than forcing theirinhabitants to move.71

The first part of this section reviews lessons from theprevious section and presents generic lessons for citygovernments. This is followed by an assessment of adapta-tion responses in the various economic sectors. The thirdpart takes a closer look at how to build resilience at the locallevel, while the fourth part reviews the links between

adaptation planning and local governance. The final part ofthis section presents UN-Habitat’s Cities and ClimateChange Initiative as an illustration of how internationalagencies can support climate change adaptation initiatives atthe local level.

Generic lessons for city governments

Table 6.5 provides examples – for city governments – of howclimate change adaptation needs to develop preparednessgoals and actions for each priority planning area. The tableaddresses this by focusing on three kinds of impacts that willaffect many cities: constraints on freshwater supplies; stormand floodwater management; and impacts upon publichealth, such as extreme heat and higher risks from diseasesspread by certain vectors. The diversity of needed actionsalso highlights how many different departments of citygovernment need to be involved and to be able to worktogether.

Drawing on the examples provided in this chapter, itis possible to identify certain key components for developingcity adaptation strategies:

Climate changeadaptation needs todevelop preparedness goalsand actions for eachpriority planningarea


Priority Preparedness goal Preparedness actionsplanning area

Addressing Expand and diversify water supply. • Develop new groundwater sources.constraints on • Construct new surface water reservoirs.freshwater supply • Enhance existing groundwater supplies through aquifer storage and recovery.

• Develop advanced wastewater treatment capacity for water reuse.Reduce demand/improve leak • Increase billing rates for water (possibly with a pricing structure that charges more management. for high consumption).

• Change building codes to require low-flow plumbing fixtures (e.g. shower heads that cut water use).

• Provide incentives (e.g. tax breaks, rebates) for switching to more water-efficient processes.

• Reduce leakage and unaccounted for water.Increase drought preparedness. • Update drought management plans to recognize changing conditions.Increase public awareness about • Provide information on climate change impacts upon water supplies and how impacts upon water supplies. residents can reduce water use – for instance, in leaflets sent to water consumers with

their bills, newsletters, websites, local newspapers.Storm and Increase capacity to manage storm • Increase capacity of storm water collection systems and ensure their maintenance floodwater water. (which usually includes a need to extend solid waste collection services to all districts).management • Modify urban landscaping requirements to reduce storm water runoff.

• Preserve ecological buffers (e.g. wetlands).Reduce property damage from flooding. • Move or abandon infrastructure in hazardous areas.

• Change zoning to discourage or prevent development in flood-hazard areas.• Update building codes to require more flood-resistant structures in floodplains.

Improve early warning systems for • Increase the use of climate and weather information in managing risk and events – storm and flood events. including the systems that ensure populations at risk get warnings and are able and

willing to move temporarily to safe locations when needed.• Update flood maps to reflect changes in risk associated with climate change.

Public health Reduce impacts of extreme heat events. • Ensure effective early warning systems for extreme heat events with particular attention to reaching those most at risk.

• Consider what measures can serve those most at risk with particular attention to those living in heat islands and those most vulnerable to heat stress; can include opening ‘cooling’ centres during extreme heat events with provision to encourage and support those at risk to move there.

• Encourage and promote modifications to the built environment that reduce heat gain, especially the heat-island effect.

• Adopt measures within urban centres to reduce urban temperatures, including protection of open space, green space and use of shade trees.

Improve disease surveillance and • Ensure effective surveillance systems for known diseases and potential diseases protection. moving into the area, and act upon disease prevention and prepare healthcare system to

respond.• Increase public education on disease prevention for vector-borne diseases and other

diseases that could increase as a result of climate change.

Source: adapted from ICLEI, 2007

Table 6.5

Examples of climatechange preparednessgoals and actions

• Build commitment among different stakeholders. This isan essential first stage. There is a need to get an officialrecognition by and within cities that climate changeimpacts need to be considered. This has to includebuilding knowledge and commitment within the differ-ent departments of local government, many of whommay see climate change adaptation as drawing resourcesor attention away from their sectors.72 Without thecommitment of a range of individuals, groups andsectors, it is impossible to address the multiple cross-cutting aspects of adaptation. It is also clear fromspecific examples of cities developing adaptation strategies that particular individuals had important rolesin initiating this – for instance, a mayor or a senior civilservant – although, of course, its success depends onothers responding positively.

• Develop or expand the information base on currentconditions. An important part of this is considering theimpact of past extreme weather and other disasters ineach city or municipality. This should seek as muchdetail as possible, ensuring the inclusion of ‘small disas-ters’ (disasters that do not get included in internationaldisaster databases), and could draw on the DesInventarmethodology developed in Latin America and nowwidely applied elsewhere, which looks more intensivelyat disasters in any locality and includes ‘smalldisasters’.73

• Initiate risk/vulnerability assessments for the city. Suchassessments should be built up from community anddistrict assessments (and from global and nationalprojections about climate change impacts). In manycities, this can and should include the kinds of community-driven assessments undertaken by thePhilippines Homeless People’s Federation that weredescribed earlier (see Box 6.3). It may be seen as labori-ous and time consuming; but engagements with womenand men in settlements and districts that are affectedmost by extreme weather can produce a more detailedand nuanced understanding of risk and vulnerability –and, thus, a better basis to understand what adaptationis needed – as illustrated by the experiences from theurban communities of Mansión del Sapo and Maternilloin Puerto Rico.74 Such an assessment should include asmuch geographic detail as possible. Furthermore, itneeds to link hazard maps with details of what iscurrently located within the hazardous zones – includ-ing identifying population groups or settlements most atrisk and activities that may pose particular risks (e.g.water treatment plants located in areas at risk fromflooding). It is also important that city assessment candraw data from global and national projections aboutclimate change impacts. At present, many such projec-tions are insufficient and imprecise, or at times evencontradictory, thus impeding local action. It is, forexample, difficult for local governments to plan forappropriate future land use if projections of climatechange implications are weak or contradictory.75

• Assess sector-specific vulnerability and responses. Risksfrom climate change vary greatly between sectors – and

the responsibilities for addressing them vary greatlyacross the different administrative divisions and depart-ments that make up local and extra-local governments.Adapting to climate change does not only depend on allthe key sectors and departments seeing the relevance ofactions within their jurisdictions and areas of compe-tence. It is also essential that these departments takeappropriate action. However, it is difficult to get all keyspending and investing sectors and departments to dothis – and the department or division with responsibilityfor directing attention towards climate change adapta-tion rarely has more than an advisory role and,moreover, usually has a very limited budget of its ownfor investment. It needs to convince the departmentsconcerned with public works, public health, housing,solid waste management, schools, etc. to engage withadaptation. The adaptation strategies of Durban (SouthAfrica), London (UK) and Melbourne (Australia)76

sought to make clear how the main climate threats arelinked to specific sectoral responsibilities, and this hasmade the responsibilities for adaptation much clearer.Agencies responsible for disaster preparedness responsehave particular importance – although these often needto broaden their focus beyond response to disasterpreparedness (and disaster prevention) and all that thisimplies for their engagement with city- and community-level housing and infrastructure investments. Theagencies responsible for disaster response will often seethe relevance and importance of their engagement inthis; but they too often lack influence and resources,especially in relation to the measures that avoid orprevent disasters.77 Utility companies, different govern-ment departments, and the private sector will all havekey roles, too, in addressing specific vulnerabilities.

• Develop strategic plans for the city as a whole and itssurrounds.78 Urban authorities should have the key rolein developing strategic plans for the city as a whole; butthis needs to be done in association with other stake-holders. These strategic plans are necessary to ensurecomplementarities and coordination between differentactivities in the urban area. Several of the most effectivestrategies described above have included strategicadaptation plans. This has been an important part of theprocess in both Cape Town and Durban (South Africa) –however, because of the commitment from the munici-pality’s Environmental Planning and Climate ProtectionDepartment, the plans have moved closer to implemen-tation in Durban. For many major cities, the strategicplans need to encompass the larger region on whoseresources and ecosystem services the city depends. Thisis more easily done when the area under the jurisdic-tion of the city government includes this larger region;the added complexities politically and institutionallywhere this is not so are obvious.

• Support local responses to climate change. Many of thekey adaptations to climate change will require individualand collective action at the community level to buildresilience and prevent harmful effects. It is widelyaccepted that much adaptation will be undertaken

Risk/vulnerabilityassessments for thecity … should bebuilt up fromcommunity anddistrict assessments(and from global andnational projectionsabout climatechange impacts)

Urban authoritiesshould have the keyrole in developingstrategic plans forthe city as a whole;but this needs to bedone in associationwith otherstakeholders


incrementally by individuals and households, and thatcommunities and local organizations also have impor-tant roles in this. There are many examples ofcommunity-driven ‘slum’ upgrading that greatly reducedenvironmental health risks; if served with appropriateinformation and support, these can include attention toclimate change risks (which in the next few decades aremostly increased risk levels from hazards alreadypresent). The above examples from the Philippines (seeBox 6.3) show that community organizations have thecapacity to build resilience and identify appropriateshort- and long-term responses to climate events – ifthey are adequately supported by local authorities. Thislatter point is an important one; as was noted above,effective climate change strategies require a partnershipapproach – involving households and communities, butalso the various levels of government and otherpartners, including international organizations.

Adaptation responses to potential impactsin different economic sectors

It is clear from the discussion above that climate changeadaptation action is needed in almost all sectors; Table 6.6,drawn from the IPCC, provides some examples of the kindsof specific adaptation interventions needed by some of thekey sectors. Although this table does not highlight this,much of what is listed in the adaptation option/strategy willfall to local government to implement, even if it needsresources and policy and regulation frameworks from higherlevels of government.

With regard to infrastructure, most fields of infra-structure management already incorporate measures to copewith climate variability and extreme events – includingwater, sanitation, transport and energy management. What isrequired, in addition, is to include climate-proofing of infra-structure for future climate change.79 Adaptation to climatechange will typically involve increases in reserve margins andother kinds of back-up capacity, and attention to systemdesigns that allow adaptation and modifications without

What is required …is to include climate-proofing ofinfrastructure forfuture climatechange


Sector Adaptation option/ Underlying policy Key constraints to Key opportunities to strategy framework implementation implementation

Water Expanded rainwater National water policies and Financial and human Integrated water resources harvesting; water storage integrated water resources resources; physical barriers. management; synergies with and conservation techniques; management; water-related other sectors.water reuse; desalination; hazards management.water-use and irrigation efficiency.

Infrastructure and Relocation; sea walls and Standards and regulations Financial and technological Integrated policies and management; settlements storm surge barriers; dune that integrate climate change barriers; availability of synergies with sustainable

reinforcement; land considerations within design; relocation space. development goals.acquisition and creation of land-use policies; building marshlands/wetlands as codes; insurance.buffer against sea-level rise and flooding; protection of existing natural barriers.

Human health Heat–health action plans; Public health policies that Limits to human tolerance Upgraded health services; improved emergency medical services; recognize climate risk; (vulnerable groups); quality of life.improved climate-sensitive strengthened health services; knowledge limitations; disease surveillance and regional and international financial capacity.control; safe water and cooperation.improved sanitation.

Tourism Diversification of tourism Integrated planning (e.g. Appeal/marketing of new Revenues from ‘new’ attractions; attractions and revenues; carrying capacity; linkages attractions; financial and involvement of wider group of shifting ski slopes to higher with other sectors); financial logistical challenges; potential stakeholders.altitudes and glaciers; artificial incentives (e.g. subsidies and adverse impact upon other snow-making. tax credits). sectors (e.g. artificial

snow-making may increase energy use).

Transport Realignment/relocation; Integrating climate change Financial and technological Improved technologies and design standards and considerations within barriers; availability of less integration with key sectors planning for roads, rail and national transport policy; vulnerable routes. (e.g. energy).other infrastructure to cope investment in research and with warming and drainage. development for special

situations (e.g. permafrost areas).

Energy Strengthening of overhead National energy policies, Access to viable alternatives; Stimulation of new technologies; transmission and distribution regulations, and fiscal and financial and technological use of local resources.infrastructure; underground financial incentives to barriers; acceptance of cabling for utilities; energy encourage use of alternative new technologies.efficiency; use of renewable sources; incorporating sources; reduced dependence climate change within on single sources of energy; design standards.increased efficiency.

Source: based on Parry et al, 2007b, Table SPM4

Table 6.6

Examples of specific adaptation interventions by sector

major redesigns and that can accommodate more extremeconditions for operations.80 Infrastructural adaptation cantake one of several forms: building retrofitting and strength-ening; lifeline infrastructure strengthening; and hazardmodification.81 In Georgetown (Guyana), detailed cost-benefit analyses have been used to assess the mostimportant and cost-effective infrastructural responses toclimate change. These have been complemented by a morequalitative approach that seeks to identify costs and benefitsfrom a non-monetary perspective.82

Infrastructure can be adapted in a variety of ways, notall of which require complicated technological solutions.Planned adaptation to sea-level rise can involve retreat,accommodation or infrastructural solutions (as is illustratedin Figure 6.3). However, in practical terms, there are strongsocial, political and economic reasons for protecting landthat has already been developed in densely settled urbanareas.

There are a growing number of examples of urbanareas that have adopted infrastructural solutions to addressparticular aspects of climate change (although it should benoted that some of the examples provided below, such asthat of Venice, are related to natural processes that wouldrequire attention even without the added risk brought aboutby climate change):

• Responses to flooding. In Venice (Italy), the ModuloSperimentale Elettromeccanico (‘ExperimentalElectromechanical Module’) involves the constructionof 79 gates at three lagoon inlets: when waters rise1.1m above ‘normal’, air will be injected into thesehollow gates, causing them to rise and preventing thecity from flooding. In many developing countries, fewprojects have been implemented; although proposedstrategies exist for Nam Dinh Province (Viet Nam),including building reservoirs to retain floodwater,strengthening dyke systems to resist higher flood levels,and constructing emergency spillways along dykes forselective filling of flood retention basins.83

• Water conservation. Singapore has a Four National TapsStrategy to ensure the future supply of water. The first‘tap’ is the supply of water from local catchments basedon an integrated system of 15 reservoirs and an exten-sive drainage system to channel water into these; thesecond is imported water from Johor (Malaysia); thethird is high-grade reclaimed water; and the fourth isdesalinated water.84

• Reducing urban temperatures. ‘Cool roofs’ and ‘porouspavements’ are being used in Vancouver (Canada) toreduce the urban heat island. These are covered withlight-coloured water sealants that reflect and radiatemore heat than dark surfaces, thus reducing the needfor mechanical cooling systems.85

The World Bank and the Asian Development Bank have beendeveloping their capacity to design and deliver infrastructurethat will meet the needs of climate change.86 Investment ininfrastructure can support sustainable socio-economic devel-opment, and can also facilitate reconstruction and recovery.

However, infrastructural investment is fraught withchallenges. Large-scale interventions of this type havefrequently failed to take into account the particular socialand economic context of the areas in which they are imple-mented, with negative social consequences, including forcedrelocations87 and provision of services in a way that fails tomeet the needs of low-income groups.

Building resilience

The many measures by which low-income households andcommunities try to cope with extreme weather, and theirimportance in reducing risks, has been discussed at lengthalready. Many of these measures would fit with the defini-tion of resilience given by the IPCC: the ‘ability of a social orecological system to absorb disturbances while retaining thesame basic structure and ways of functioning, the capacityfor self-organisation, and the capacity to adapt to stress andchange’.88 Indeed, the many examples of simple pragmaticways of coping with floods such as having shelves high upwalls above anticipated flood levels, and furniture (oftenraised on bricks) on which the residents can sit or sleepcould be included in this definition.

There are important components of resilience beyond‘hard’ infrastructure – in part because hard infrastructurewill be unable to remove or greatly reduce many risks,especially if the governments of the world do not reachagreement on needed emissions reduction soon.89 Thus,resilience is also a capacity to live in hazardous, changing anduncertain environments90 and through assets, socialnetworks and partnerships to have the needed capacity to (inthe words of the IPCC) ‘absorb disturbances while retainingthe same basic structure and ways of functioning’.91

Perhaps the building of resilience should be under-stood as a way of enabling not only coping with added shocksand stresses, but also addressing the myriad challenges thatconstrain lives and livelihoods. Thus, a key part of buildingresilience is facilitating poverty reduction and more generalimprovements to the quality of human lives.92

Many interventions being undertaken in urban areasaround the world – by local, municipal, national and interna-tional stakeholders – contribute to building this resiliencethrough improving housing, infrastructure and services,particularly for the urban poor. Addressing the challenges of

Planned adaptationto sea-level rise caninvolve retreat,accommodation orinfrastructuralsolutions

The building ofresilience should beunderstood as a wayof enabling not onlycoping with addedshocks and stresses,but also addressingthe myriadchallenges thatconstrain lives andlivelihoods


Figure 6.3

Adapting infrastructureto sea-level rise

Source: Parry et al, 2009, p63

Planned retreat

Accommodation

Protection–�hard–�soft

climate change adaptation may not be the explicit or primarypurpose of these activities; but, in practice, they provide anessential foundation for the process of adaptation. Indeed,for many cities in developing countries, this is likely to bethe single most important component of an overall adapta-tion strategy.

In addition, many of these urban areas already experi-ence an ‘adaptation deficit’. The infrastructure isinsufficient to cope with present climatic conditions – letalone those that will arise as a result of climate change.Existing storm drains, water supply networks and transportinfrastructure may have been developed decades ago toserve a much smaller population – and before these can be‘adapted’ to deal with future climate threats, they must firstbe upgraded to deal with current conditions. In this respect,it is helpful to consider Stern’s definition of adaptation:‘development in a more hostile climate’.93 Many of theadaptation needs for urban areas in developing countriesare based on the need for development that takes a changing climate into account.

A wide range of urban improvement programmes andprojects around the world can be seen as contributing toreducing the infrastructure deficit and increasing urbanresilience to climate change. Global initiatives to improveurban housing (such as UN-Habitat’s World Urban Camp-aign94 and its predecessor, the Global Campaign for SecureTenure) and provide appropriate plans for urban develop-ment (such as the City Development Strategies95 promotedby the Cities Alliance) can form the basis for building urbanresilience. However, these large-scale responses requirecareful analysis to ensure that they remain genuinely pro-poor and meet the needs of the most vulnerable urbanresidents.96

Many communities are already involved in activitiesthat will build the resilience of individuals and households.For many low-income urban residents, savings schemes97

form the basis for this resilience. The practice of savingregularly with such schemes has both instrumental benefits(the ability to access funds when necessary) and organiza-tional benefits (the relationships of trust built up aroundsmall savings groups are central to identifying solutions tolarger problems). Small-scale loans repaid over very shorttime periods provide much needed capital for livelihoodactivities. They can develop into small-scale loans to helpimprove or extend housing. Furthermore, organized savingsgroups have also demonstrated the ability to negotiate forand acquire new land sites that are not vulnerable to climatethreats, such as flooding and landslides, upon which to buildsecure housing and thus provide protection against short-and long-term climatic threats.

Insurance policies for houses, possessions andbusinesses contribute to resilience where they providecompensation to those whose homes, possessions andbusinesses have been damaged or destroyed. They could alsocontribute to building resilience by including financial incen-tives (such as reduced premiums) for those who havereduced their risks. However, this will not serve thoseunable to access the formal housing market and/or thosewho cannot afford insurance. For urban centres in develop-

ing countries, this means most of the population and mostenterprises. Insurance companies will not offer insurancecoverage to cities or to households and businesses on citysites at high risk from climate change because of inappropri-ate locations or deficits in infrastructure.

Adaptation planning and local governance

Drawing on the descriptions of household, community-basedand local government actions for adaptation in previoussections, this section considers the relative roles for commu-nity-based adaptation and for adaptation planning andgovernance. These tend to operate at different scales(although often with cross-scale linkages) and to involve adistinct balance between individual and collective action,and between behavioural and structural (in terms of bothhousing and infrastructure) responses. Yet, these frame-works should be viewed as complementary rather than asmutually exclusive. As is evident from a wide range ofstudies on addressing urban environmental challenges morebroadly, there is a need to link structural and behaviouralresponses. For example, individuals and community groupsin cities with limited investment capacities may be bestplaced to devise the most appropriate sanitation solutions forthemselves and their neighbourhood – but these are of littleuse without larger investments at the scale of the town orcity to ensure convenient and easily accessed water suppliesfor personal hygiene and appropriate provision for theremoval of human waste.98 Conversely, large-scale infra-structural developments to improve drainage and reduceflooding require the knowledge and expertise of engineers;but these interventions will have little value if they do nottake into account the needs of those in informal settlementsand the social and behavioural norms and expectations ofurban residents. Drainage systems also have their capacity toprotect cities from flooding much reduced if they are notmaintained (which may need community support) andprotected from encroachment.

In urban areas of developed countries, citizens take forgranted that a range of local structures and organizationsprovide protection from environmental hazards and help tocreate resilience to potential disasters. It is assumed thatthese will also provide for adaptation to climate change. Here,residents do not need to organize themselves to clear drainsand collect solid wastes; these are tasks that local authoritiesdo or organize. These urban areas have infrastructure andservices that protect them from environmental hazards(through, for instance, the provision of safe water supplies,sewers and drainage) or help them to cope when illness orinjury occurs (e.g. through well-managed healthcare andemergency service systems).99 In urban areas in developingcountries, these facilities and services are frequently absentor they serve only a proportion of the population. Localgovernments lacking capacity and funding, and with largeinfrastructure and service deficits need the contributionsthat community-based organizations can bring. There are alsothe exceptional local governments that have shown how100 –even with limited resources – effective governance andplanning can work towards facilitating urban adaptation.

150

A wide range ofurban improvementprogrammes andprojects around theworld can be seen ascontributing toreducing the infrastructure deficitand increasing urbanresilience to climatechange

For many low-incomeurban residents,savings schemesform the basis for …resilience

Exceptional localgovernments … haveshown how – evenwith limitedresources – effectivegovernance andplanning can worktowards facilitatingurban adaptation

Cities and Climate Change

Planning for adaptation can take place at a range ofscales. As described in the previous section, some urbanareas have developed plans for adaptation at both the cityand sectoral levels as a key component of their preparationfor climate change. The examples of Cape Town and Durban(South Africa) showed how large urban areas can developmunicipal-level plans for adaptation that take into account arange of social and environmental challenges.101 Theseprovide the framework within which local governmentdepartments, the private sector, civil society and individualscan prepare and implement their contributions to strategiesfor adaptation within development or investment plans.There are other examples where city governments havesuccessfully avoided large-scale settlement by low-incomepopulations on dangerous sites that would be at risk fromclimate change. In Manizales (Colombia), local authorities,universities, NGOs and communities worked together todevelop programmes aimed not only at reducing risks, butalso at improving the living standards of the poor and atprotecting fragile ecological areas. Households were movedoff the most dangerous sites, but rehoused nearby, and mostof the former housing sites were converted into eco-parkswith strong environmental-education components.102 In Ilo(Peru), long-term engagement by consecutive democraticallyelected mayors have improved water supply, sanitation,electricity provision, waste collection and public space.Despite the population increasing fivefold between 1960and 2000, no land invasion or occupation of risk-prone areasby low-income groups looking for housing has taken place, aslocal authorities have implemented programmes to accom-modate this growth in a sustainable way.103

There are also the examples of resident groups incities that organized to influence the future development oftheir city along more ecologically sustainable paths. Theseinclude some where climate change adaptation has beenimportant – as in the city of Tatabánya (Hungary), some50km from the capital city of Budapest, which offers anexample of how community members can be an importantdriver and resource in climate adaptation (see Box 6.6).104

Participatory budgeting has become one of the best knownand most widely applied forms of citizen engagement in theplans and priorities of city governments,105 and in somecities, this engagement has included a strong focus onenvironmental issues.106

In London (UK) (see Box 6.5) and Bangkok (Thailand)(see Table 6.2), the approach to climate change adaptationplanning has been to identify particular sectors that are ‘atrisk’ and develop plans to address each of these, and withthe delegation of responsibility to appropriate agencies. Thisrequires an effective system of oversight and control, andrelies on these agents having sufficient financial and techni-cal capacity to make the appropriate investments andinterventions. In London, strategies are being developed toaddress the three key climate risks affecting the city – flood-ing, drought and overheating. Bangkok will be vulnerable toa similar set of risks, and the Bangkok MetropolitanAdministration has proposed adaptation measures to betaken by the community infrastructure sector, the businessand commercial sector, and the general population.

Urban areas on Mexico’s Yucatan coast have beeninvolved in a process of social learning for climate-proofing,based on bringing together a range of stakeholders.107 Thisinvolves a three-stage process of consciousness, institutional-ization and implementation:

• Consciousness is the process of reflection onestablished norms and practices with the aim of gener-ating new visions.

• Institutionalization is the process of changing stakehold-ers in urban governance to facilitate new norms andpractices.

• Implementation is the capacity to enact new practicesand activities.

Social learning by civil society is seen as an essential pre-requisite to effective adaptation planning. This is particularlyso in a context where the government is constrained by ahighly competitive and dynamic political culture, with politi-cians and officials coming in and out of office frequently andseldom building on past knowledge or initiatives.

Urban adaptation planning is therefore intrinsicallylinked with local governance. A study of ten Asian citiesfound that preparation for climate change was stronglylinked with climate-resilient urban governance.108 Thisincludes decentralization and autonomy, accountability andtransparency, responsiveness and flexibility, participationand inclusion, and experience and support. Urban gover-nance systems that exhibit these characteristics are betterable to build resilience through having more effective finan-cial and technical management capacities in ‘climate-sensitive’ sectors such as waste, water and disaster manage-ment. Responsiveness and flexibility are crucial, given the

There are …examples where citygovernments havesuccessfully avoidedlarge-scalesettlement by low-income populationson dangerous sitesthat would be at riskfrom climate change

Urban adaptationplanning is … intrinsically linkedwith localgovernance


Box 6.6 Citizen-driven city adaptation in Tatabánya, Hungary

Tatabánya is a former mining and industrial town that has approximately 72,000 residents andwas known for its high levels of pollution. The residents have formed three groups, eachinvolved in promoting local sustainability:

1 The focus of the ‘inhabitants group’ is to develop a new vision for the future of the city.They serve in a representative capacity in public decision-making and through their effortshave helped to promote communication between residents and public officials by ensuringthat local interests are known.

2 The ‘local council of pupils group’ is made up of student representatives who engage in avariety of tasks, including participating in local decision-making.

3 The ‘local climate group’ is comprised of individuals from all walks of life, includingstudents, pensioners, doctors, nurses, teachers, engineers, scientists, public officials, heads ofcompanies and inhabitants. Among their many accomplishments, they have implemented aheat and ultraviolet light alert programme, organized teams to assist in the development ofa local climate strategy, initiated a call for tenders on energy-efficient housing, establishedemissions reduction targets, and implemented educational and information programmes.

What is perhaps most noteworthy of the Tatabánya experience is the commitment of itsresidents to their city and to addressing both immediate issues and good environmentalperformance in relation to global systems.

Sources: Moravcsik and Botos, 2007; Carmin and Zhang, 2009

limited predictability of the consequences of climate change.At the same time, the involvement of the poor and marginal-ized groups in decision-making, monitoring and evaluation iskey to improving the living conditions of these groups. In thecontext of Mexico, it has been argued that the quality of thegovernance process is the most important component forenabling climate change adaptation.109 The need to adapt toclimate change and the need to adapt governance systems tobe more responsive and effective are therefore closelylinked.

Table 6.7 highlights the range of roles that city ormunicipal governments have in climate change adaptation. Itis a reminder of how much adaptation depends on actionwithin many different sectors or parts of local govern-ment.110 This means that adaptation planning needs supportnot only from public works departments and from develop-ment planning and development control, but also from thedepartments dealing with environmental health, publichealth, and social and community services (including trans-port and public space management, and emergencyservices), as well as those dealing with finance and disastermanagement.111 Adaptation to climate change is often takento mean protection against likely changes (e.g. betterdrainage systems or coastal defences); but it should alsoinvolve three other components listed in Table 6.7: damagelimitation measures taken just before an extreme event (thathas the potential to cause a disaster), immediate post-extreme event response, and rebuilding. There is also arange of measures that local governments can take thatsupport resilience at the household and community levels.This includes slum and squatter upgrading and schemes thathelp those with limited incomes to afford to buy, build or

rent safer, better served accommodation (although to beeffective for adaptation, these need to be guided by climatechange risk assessments and appropriate responses). It alsoincludes measures to strengthen or support livelihoods andfood security for low-income groups. Urban food securitydepends on households being able to grow or afford foodwithin other needs that have to be purchased.112 The extentof food insecurity among low-income households in urbanareas is given too little consideration,113 which also meansthat their vulnerability to the impacts of climate change onagriculture is probably underestimated.

Measures to support resilience include more effectiveand accessible healthcare services and emergency responseservices that are prepared for the scale and nature ofclimate-related (and other) potential disaster risks. It alsoincludes an early warning system that actually reaches allthose in need with appropriate information, combined withknowledge of what to do and where to go – and provision toensure that all can move to identified safe places, when andwhere needed. It also means a capacity to respond afterdisasters – as in the measures listed in Table 6.1 for immedi-ate post-disaster response and rebuilding. Within this, thereis a clear need for all measures taken to address gender-specific issues of risk management and adaptation, fromshelter management to empowerment, and inclusion ofwomen in decision-making at all scales for stronger emphasison long-term and risk-averse initiatives.

UN-Habitat’s Cities and Climate Change Initiative114

The UN-Habitat Cities and Climate Change Initiative

The involvement ofthe poor and marginalized groupsin decision-making… is key to improving the livingconditions of thesegroups

There is … a rangeof measures thatlocal governmentscan take thatsupport resilience atthe household andcommunity levels


Role for city/municipal government Long-term Pre-disaster Immediate post- Rebuildingprotection damage limitation disaster response

Built environmentBuilding codes High High* HighLand-use regulations and property registration High Some HighPublic building construction and maintenance High Some HighUrban planning (including zoning and development controls) High High* HighInfrastructurePiped water, including treatment High Some High HighSanitation High Some High HighDrainage High High** High HighRoads, bridges, pavements High High HighElectricity High Some? High HighSolid waste disposal facilities High Some? HighWastewater treatment High HighServicesFire protection High Some High SomePublic order/police/early warning Medium High High SomeSolid waste collection High High** High HighSchools Medium MediumHealthcare/public health/environmental health/ambulances Medium Medium High HighPublic transport Medium High High HighSocial welfare (includes provision for childcare and old-age care) Medium High High HighDisaster response (over and above those listed above) High High

Notes: * It is important that these do not inhibit rapid responses.** Clearing/de-silting of drains and ensuring collection of solid wastes has particular importance just prior to extreme rainfall; many cities face serious flooding from extreme rainfallthat is expected (e.g. the monsoon rains) and this is often caused or exacerbated by the failure to keep storm and surface drains in good order.

Source: Satterthwaite et al, 2009c

Table 6.7

Adaptation to extremeweather: The role ofcity/municipal governments

provides an illustration of how international agencies cansupport local adaptation action. It aims to strengthen theclimate change responses of cities and local governments.The initiative is currently being piloted in four cities –Esmeraldas (Ecuador), Kampala (Uganda), Maputo (Mozam-bique) and Sorsogon City (the Philippines).115 This initiativebrings together local and national governments, academia,NGOs and international organizations to alert cities to theactions that they can take to respond to climate change. Keyprogramme components that are being encouraged foradaptation to climate change include advocacy and policychange, the development and use of toolkits, and knowledgemanagement and dissemination. An important component inthis project is the creation of a global network of citiesworking on adaptation issues, among whom knowledge canbe generated and shared.

The four pilot cities in this initiative face a range ofchallenges related to climate change. Sorsogon City, Maputoand Esmeraldas are all coastal cities affected by frequentflooding and at risk from sea-level rise. In addition, Sorsogonis at risk from tropical cyclones; Esmeraldas has many house-holds living on hillsides and riverbanks; and the protectivemangroves around Maputo are disappearing. Kampala islocated inland, but is also affected by flooding and the degra-dation of fragile hill slopes. In all cases, these challenges arecompounded by inappropriate management of naturalresources and inadequate urban infrastructure.

Various adaptation responses are being planned andimplemented in these cities in association with the Citiesand Climate Change Initiative (see Table 6.8). Some of theseare associated with broader environmental managementprojects which will simultaneously improve the resilience ofcommunities and the urban area to climate change: thereconstruction of the National Disaster ManagementInstitute in Mozambique will help to improve disaster riskreduction in Maputo and elsewhere in the country; and theflood prevention programme for the Teaone River inEsmeraldas will help to reduce flooding. Other activitiesinvolve building networks and capacity: in Kampala, it isproposed to establish a climate change network of variousstakeholders addressing climate change, whereas in Maputoit is proposed to support collaboration between the local

government and a range of other partners. Strengthening thecapacity of local authorities to address climate change is alsoa key activity in all four cities – both in terms of awareness ofthe issues and potential responses to these.

FINANCING ADAPTATIONIn terms of financing for climate change adaptation, thereare the two main issues that have to be addressed up front:

1 Will funds will be available to cover the cost of adapta-tion for urban areas?

2 Is there local capacity in place to use such funds in sucha manner that the needed adaptation can take place?

International debates and discussions have tended to focuson the first of these, not the second. Funding for adaptationin developing countries comes (and will come) primarily from two main sources: the dedicated climate change funds available under the United Nations Framework Conventionon Climate Change (UNFCCC) (see Box 2.2) and throughoverseas development assistance. As noted in Chapter 2, theissue of funding has been high on the agenda in internationalclimate negotiations. Ideally, there is wide agreement thatinternational funding for climate change adaptation should beadequate to the task at hand, and should explicitly allocate afair share of resources to urban settlements. However, inpractice, the funds available are, at present, inadequate;furthermore, these funds do not target urban settlements.116

Moreover, the first consistent approach to identifying adapta-tion priorities, the NAPAs, generally missed urban priorities.So far, urban priorities also seem to be absent from thefunding allocated through the Adaptation Fund.117

Adaptation to climate change has become an impor-tant priority in the international climate change negotiationsduring recent years. At the latest meeting of the COP (2010,Cancún, Mexico), Parties reiterated the importance ofadaptation and agreed that:

adaptation is a challenge faced by all Parties,and that enhanced action and international

Funding for adaptation in developing countriescomes … primarilyfrom … thededicated climatechange funds available under the…UNFCCC … andthrough overseasdevelopment assistance

In practice, thefunds available are,at present, inade-quate; furthermore,these funds do nottarget urban settlements


City Proposed activities

Esmeraldas • Zoning of riverbanks and preparation of a participatory land-use plan.• Preparation of a risk management plan.• Implementation of an environmental management plan for the Teaone River (including solid waste management and riverside

rehabilitation through reforestation).Kampala • Establishment of national and city climate change network.

• Increasing awareness and capacities of Kampala City Council.• Increasing synergies between national and local climate change policies and programmes.

Maputo • Strengthening disaster risk preparedness at the community level.• Localizing the national climate change adaptation plan.• Promoting policy dialogue to strengthen the government response capacity to floods.• Education and public awareness campaigns to create climate change awareness.• Capacity-building with local government and a wider range of partners.

Sorsogon • Development of knowledge products for sharing and cross-fertilization of ideas.• Demonstration of innovative technologies for climate-resilient human settlements, particularly in low-lying urban coastal areas.• Development of the capacity of the city government.• Advocacy, awareness-raising and partnership building on climate change with stakeholders and the general public.

Source: UN-Habitat, 2008a

Table 6.8

Proposed and plannedactivities in the pilotcities of the Cities andClimate ChangeInitiative

cooperation on adaptation is urgently requiredto enable and support the implementation ofadaptation actions aimed at reducing vulnerabil-ity and building resilience in developing countryParties, taking into account the urgent andimmediate needs of those developing countriesthat are particularly vulnerable.118

The Cancún Agreements further reaffirm the commitmentmade by developed countries to expand the scale of fundingavailable for adaptation during COP-15, including throughthe US$100 billion which is to be mobilized by 2020 tosupport action in developing countries. However, theambiguity on where the increased funding will actually comefrom remains unresolved. Furthermore, the CancúnAdaptation Framework was established to further enhanceaction on adaptation.

As noted in Box 2.2, international funding for adapta-tion through the UNFCCC includes the Special ClimateChange Fund, the Least Developed Countries Fund and theAdaptation Fund. The Adaptation Fund was established tofinance adaptation projects and programmes in developingcountries, with particular attention to those countries thatare particularly at risk from the adverse effects of climatechange. It is likely to have particular importance because partof its funding comes from a levy on the project activities ofthe Clean Development Mechanism, and this should give it aconsiderable and guaranteed source of funding. Thus, unlikethe other funds, it is not reliant on negotiating funding fromdonor agencies. It also has a governance structure in whichdeveloping countries have more influence; its independentboard has representation from each of the major regions, aswell as special seats for the least developed countries andthe small island developing states.119

A review of financing arrangements for adaptation120

suggested that there is an opportunity for complementaritybetween this Adaptation Fund and overseas developmentassistance. For example, the review suggested that overseasdevelopment assistance can help to focus on the drivers ofvulnerability that are associated with weak institutionalcapacity, while the Adaptation Fund supports developingcountries’ broader climate risk management strategies. It alsosuggested that the bilateral and multilateral donor agenciescan help to build the necessary local and national institutionalcapacity to receive and make good use of support from theAdaptation Fund. However, this also presupposes a capacityamong such agencies to work with civil society and localgovernments, which is often not present.

This mix of funding might also overcome thecontentious issue of the boundary between climate changeadaptation and development. Development should certainlyinclude ‘adaptation’ to all disaster and environmental healthrisks, including those to which climate change does notcontribute or only partially contributes. The large climatechange adaptation deficit in most developing countries isalso a development deficit. This raises the questions ofwhether funding for climate change adaptation shouldinclude funding for removing this development deficit(which also proves to be an adaptation deficit) or not. In

theory, the governments of developed countries thatcontribute funding to adaptation will want this to beseparated from aid budgets and focus specifically on climatechange adaptation. Yet, how can a city adapt to climatechange if half of its population live in informal settlementsthat lack the most rudimentary infrastructure and services?And how can funding for adaptation be managed if there isone funding stream and set of agencies for putting in placeneeded infrastructure and another for adapting this infra-structure?

Attention should also be paid to the relative costs ofmitigation and adaptation. The estimates for the costs ofmitigation (achieving the needed reductions in global GHGemissions) appear very high. Many estimates for the costs ofadaptation – including those produced by the UNFCCC (seeTable 6.9) – are much lower. Based on this, it could beargued that mitigation costs can be reduced by funding foradaptation that allows a less rapid reduction in global GHGemissions. However, if the estimates for the costs of adapta-tion are far too low and consideration is given to thedifficulties in overcoming the lack of adaptive capacity withinlocal governments, it changes the balance. A more realisticassessment of the incapacity and unwillingness of mostnational, city and municipal governments within developingcountries to actually implement needed adaptation measuresmeans that mitigation should receive a much higher priority.In the end, the discussion boils down to the willingness ofgovernments in developed countries (and some industrial-ized developing countries) to reduce the carbon-intensiveconsumption patterns of their citizens121 to benefit others –especially future generations and those who are most at riskand most vulnerable to climate change (most of whom live indeveloping countries).

This section focuses on the costs of adapting infra-structure to the potential future impacts of climate change.It also includes a discussion of the very large costs involvedin remedying the large deficits in infrastructure in urbanareas in most developing countries – for instance, the lack ofstorm and surface drains, paved roads and footpaths, andreliable piped water supplies. Remedying these deficits maynot be considered as climate change adaptation; but withoutremedying these deficits, it is not possible to build resilienceto most climate change impacts. Also, if the costs of remedy-ing these infrastructure deficits are considered as part ofclimate change adaptation, the costs of adaptation increasevery considerably.

It is, however, important to note that the discussionbelow does not include a discussion of many institutionaland social adaptation costs. Nor does the discussion touchon the issue of residual damage: the cost incurred in anincreasing number of locations that become permanentlybeyond adaptation – because adaptation is considered tooexpensive or technically unfeasible. Some such challengesare addressed in the next section.122

The costs of adaptation

The basis for accurate national and global estimates for thecosts of adaptation does not exist. The costs of adaptation

The CancúnAgreements …reaffirm the commitment madeby developedcountries to expandthe scale of fundingavailable for adapta-tion during COP-15

The large climatechange adaptationdeficit in mostdeveloping countriesis also adevelopment deficit

If the costs ofremedying … infrastructuredeficits are consid-ered as part ofclimate changeadaptation, the costsof adaptationincrease veryconsiderably


are so local, so specific to location and to existing levels ofhousing and infrastructure quality and governance capacity –and there are few examples of locally determined adaptationcosts upon which to base national or global estimates. Costestimates are also greatly influenced by the form that adapta-tion takes – for instance, what safety margins are built intonew infrastructure and what balance is achieved betweenprotection and accommodation.

Most global estimates of the cost of adaptation arebased on the costs of climate-related disasters; but these areknown to form a very inadequate basis for this. One reasonfor this is that the cost estimates of climate-related disastersdo not include most disasters because they have a very highthreshold for a damaging event to be included in theirconsiderations.123 Where careful local or national reviews ofdisaster events and their impacts have been carried out,these highlight the very large underestimates, especiallywith regard to deaths and serious injuries.124 There is alsothe problem of assigning costs to disasters based on thevalue of the properties destroyed – so a disaster that destroysthe homes and possessions of hundreds or thousands ofhouseholds does not appear ‘serious’ because the monetaryvalue of their homes in informal settlements is low and theyhad no insurance. It is odd, indeed, to base any estimates foradaptation costs on what insurance companies have had topay out for extreme weather disasters if almost all thoseaffected by these disasters do not have insurance.

Most estimates for the costs of adaptation that arerelevant to urban areas are based on the costs of adaptinginfrastructure, and thus include roads (of all sizes, fromhighways to streets and lanes) and bridges, railways, airports,ports, electric power systems, telecommunications, water,sewerage, and drainage/wastewater management systems.The definition of infrastructure is sometimes broadened toinclude services which make economic and social activitiespossible – so it would include services such as public trans-port, healthcare, education and emergency services (whichcollectively are sometimes termed social infrastructure). Aproportion of such infrastructure is outside urban bound-aries, although almost all of it is important to the functioningof urban economies. There is also all the ambiguity in whatgets included under infrastructure – including housing(sometimes included, sometimes excluded) and the institu-tions that operate and manage infrastructure.

The UNFCCC secretariat has made estimates for thecosts of adapting infrastructure (see Table 6.9); but it doesnot specify what is included in the term. It is also unclear asto whether housing and the institutions needed to operateand manage infrastructure are included in its estimates.125 Itmight be assumed that estimates for the costs of extremeevents that draw on records from insurance companieswould include housing; but only a very small proportion ofhouseholds in developing countries have disaster insurance(and thus have their costs included in ‘costs’ based on insur-ance claims). The destruction of, or damage to, housing isone of the most common and most serious impacts of manyextreme weather events, especially in many developingcountries. The damage to, or loss of, housing is usuallyconcentrated among low-income groups and this often also

includes loss of possessions. Only a very small proportion ofthe population in developing countries have insurance forthis. Assessing the impacts of such events in terms of thevalue of property damaged or destroyed can be misleading;an event that is devastating to the lives of very largenumbers of people (in deaths, injuries and loss of property)may have low economic impacts because of the low valueassigned to the housing damaged or destroyed.126

For infrastructure, adaptation costs should includethe costs of limiting the impacts (as well as preventingthem). For many extreme weather events in urban areas withlarge infrastructure deficits and poor-quality housing, goodearly warning systems, measures taken just before theextreme event (e.g. reducing the impact of flooding bysupporting populations in moving temporarily to high groundor safe sites) and rapid and effective post-event responses(temporary accommodation, restoring access to services,supporting rapid return to settlements damaged and support-ing rebuilding) greatly reduce the impacts upon populationsand their assets. Yet, these measures might be considered asinadequate or invalid for adaptation funding in that they arenot limiting the damage done to infrastructure. The costs ofbuilding and maintaining this capacity to reduce the impactsof extreme weather events is not included in figures forinfrastructure investments, and these costs are thus notconsidered in the UNFCCC estimates.

There is also the issue of infrastructural damage thatcannot be prevented by adaptation – the so-called ‘residualdamage’ – stemming both from conscious choice (locations/facilities/structures for which full protection is judged to betoo costly, or where adaptation is technically not feasible) orfrom incapacity on the part of those who are at risk andthose institutions which have responsibility for reducing thisrisk (local government, national governments, etc.) (seeFigure 6.4). Thus, the UNFCCC estimates for the costs ofadapting infrastructure include consideration of a limitedpart of ‘infrastructure’ that does not include social infra-structure, disaster-response infrastructure, housing and theinstitutional infrastructure needed to build, maintain andadapt infrastructure. Thus:

The UNFCCC estimate of investment needs isprobably an under-estimate by a factor ofbetween 2 and 3 for the included sectors. Itcould be much more if other sectors are consid-ered... For infrastructure it may be several timeshigher, at the lower end of the cost range.127

The destruction of,or damage to,housing is one of themost common andmost seriousimpacts of manyextreme weatherevents

The UNFCCCestimates for thecosts of adaptinginfrastructure …does not includesocial infrastructure,disaster-responseinfrastructure,housing and theinstitutional infrastructureneeded to build,maintain and adaptinfrastructure


Sector Global costs Developed countries Developing countries(US$ billion) (US$ billion) (US$ billion)

Agriculture 14 7 7Water 11 2 9Human health 5 Not estimated 5Coastal zones 11 7 4Infrastructure 8–130 6–88 2–41Total 49–171 22–105 27–66

Note: All values are in US$ at present day values. The only ‘sector’ that includes the cost of ‘residual damage’ in the aboveestimates comprises the ‘coastal zones’.

Source: UNFCCC, 2007, cited in Parry et al, 2009

Table 6.9

Annual investmentneeds by 2030 to coverclimate change adaptation costs(estimates)

The infrastructure deficit

The fact that most developing countries have very largedeficiencies in provision for infrastructure has beendiscussed in detail already. A high proportion of the urbanpopulation in Africa and Asia and a significant proportion inLatin America and the Caribbean live in homes and settle-ments with little or no infrastructure (i.e. no all-weatherroads, no drains, no piped water supplies and no provisionfor electricity). Most urban centres in developing countrieshave no sewers, including many with several million inhabi-tants.128 During the period from 2000 to 2010, the numberof slum dwellers in developing countries has increased from767 million to 828 million, and ‘short of drastic action tocurb current trend, the slum population worldwide is likelyto ... reach a total of 889 million by 2020’.129 A large propor-tion of these slums are characterized by inadequate or noprovision of basic infrastructure. The lack of provision orinadequacies in the provision of protective infrastructure isperhaps the main reason for the very rapid increase in thenumber of flood and windstorm ‘disasters’ since the 1950s.

Reviewing data on disasters also gives some indica-tions of the kinds of impacts that extreme weather eventscan have upon infrastructure – within the larger costs interms of death, injury and economic disruption – and loss oflivelihood for large numbers of people. Reviewing the ‘disas-ters’ registered on an international database130 between1996 and 2005 shows not only thousands of people killedand tens of millions affected by floods and windstorms, butalso hundreds of billions of dollars worth of damage. Forinstance, in Asia, floods and windstorms between 1996 and2005 caused over 70,000 deaths and around US$191 billionworth of economic loss. A large part of these deaths and theeconomic losses could be attributed to infrastructuredeficiencies. UNFCCC notes the following:

Evidence for the existence and size of theadaptation deficit can be seen in the mountinglosses from extreme weather events such asfloods, droughts, tropical cyclones, and otherstorms. These losses have been mounting at avery rapid rate over the last 50 years. Thisincrease is likely to be mostly due to the expan-sion of human populations, socio-economic

activities, real property, and infrastructure of allkinds into zones of high risk. Moreover, muchof this property is built at a substandard leveland does not conform even to minimal buildingcodes and standards. This widespread failure tobuild enough weather resistance into existingand expanding human settlements is the mainreason for the existence of an adaptation deficit.Real property and socio-economic activities arejust not as climate-proof as they could andarguably should be. The evidence suggestsstrongly that the adaptation deficit continues toincrease because losses from extreme eventscontinue to increase. In other words, societiesare becoming less well adapted to currentclimate.131

However, while this recognizes that there is a very largeclimate change adaptation deficit, much of which is an infra-structure and institutional infrastructure deficit, theUNFCCC report does not consider it appropriate to considerthis in estimating adaptation costs for infrastructure.132

A review of the basis used by the UNFCCC forestimating the costs of adapting infrastructure133 suggestedthat this was based on an incorrect premise – that this canbe costed by applying a small increment to existing invest-ment flows into infrastructure that is climate sensitive, withno account taken of the very large infrastructure deficits.This leads to the conclusion that most of the investmentneeded for climate change adaptation in terms of infrastruc-ture is required in developed countries, rather than indeveloping countries. It also ends up showing very smallsums needed for Africa and other places where there arevery low/inadequate investment flows into infrastructureand where many of the countries most at risk from climatechange are located. This same review also noted three otherassumptions that need to be questioned:134

1 The availability of funding from international agencies isthe ‘solution’ for adaptation. In much of Africa and Asiaand parts of Latin America and the Caribbean, localgovernments are weak, ineffective and unaccountableto local populations, so their capacity to design andimplement appropriate adaptation strategies that servethose who are most at risk from climate change must bein doubt. This is most obvious in the countries that areoften termed ‘failed states’; but it is also evident inmany other countries. External funding agencies havenot proved very effective in addressing this – or even inknowing how to address this.

2 ‘Adaptation’ and ‘development’ can be kept separate.On the ground, climate change impacts are exacerbat-ing non-climate change impacts and addressing both isinhibited by institutional/governance failures. It is diffi-cult, if not impossible, to separate what proportion ofextreme weather damage or water shortages in anylocality are caused by climate change. So much of theadaptation deficit for housing and infrastructure is alsoa development deficit.

Most of the investment neededfor climate changeadaptation in termsof infrastructure isrequired in devel-oped countries,rather than in developing countries


Figure 6.4

Adaptation costs,avoided damages andresidual damage

Source: Parry et al, 2009, p12

Low cost to avoid damage

Ratio = 1 (incremental adaptation cost: avoided damage)

High cost to avoid damage

Residual damage {

Avo

ided

dam

ages

Adaptation costs

3 NAPAs give us an idea of adaptation costs. The focus ofmost of the NAPAs is a very small part of what thesecountries will need for adaptation. NAPAs are thus not agood basis for costing adaptation costs.

The cost of addressing the infrastructure deficit

Detailed cost estimates were undertaken in selectedcountries to estimate the investments needed to meet theMillennium Development Goals between 2005 and 2015and these came to US$993 to $1047 per person.135 Aroundhalf of this was for infrastructure (including water andsanitation, energy and roads). Yet, these estimates do notaddress the elimination of all infrastructure (and other devel-opment) deficits. Many of the Millennium DevelopmentGoals are only for reducing the problem – for instance,halving the proportion of people without sustainable accessto safe drinking water and basic sanitation by 2015.Similarly, the goal for improving the lives of slum dwellerswas to reach 100 million slum dwellers by 2020, whichwould represent only around 13 per cent of the slum popula-tion in 2000 (and a much smaller percentage of the likelyslum population in 2020). Thus, the total cost to remove theinfrastructure deficit is likely to be much higher.

One recent estimate suggested that the cost ofremoving the housing and infrastructure deficit in develop-ing countries by 2030 would be some US$6.3 trillion – andthis would include US$700 billion for expanding housingand infrastructure for expanding urban populations.136

These estimates are broadly in line with estimates in the2009 report of the International Strategy for DisasterResponse137 for the investments needed to reduce thedeficit in disaster risk avoidance and risk reduction. Thissuggests that several hundred billion dollars a year arerequired to address the underlying risk factors for disasters(including those relating to climate change).

However, as was noted in the introduction to thissection, the availability of funding is only a part of thesolution, as solutions also depend on national and localgovernments having the competence, capacity and accounta-bility to make the needed investments. It is important tostress that adaptation will require very large capital sumsinvested in developing countries, but also to recognize that,at the moment, there are no reliable methodologies forestimating these costs accurately. What is more urgent andimportant is to get serious consideration given to climatechange adaptation plans and programmes for particular local-ities (including cities), and to what resources can begenerated for these locally or supported by higher levels ofgovernment. Furthermore, there is a need to consider howthese plans and programmes can be pro-poor and supportiveof general development initiatives. Based on such considera-tions, it might be possible for the international communityto arrive at a more accurate and specific understanding ofthe international funding mechanisms which are required tosupport such plans and programmes.

Thus, there is a need for detailed case studies of whatadaptation would involve in particular locations and what

component would have to be allocated to infrastructuredeficits. The studies described earlier in this chapter aremoving in this direction, although most are from cities indeveloped countries. Such studies need to consider theinfrastructure deficit and the needed institutional/gover-nance underpinning for addressing the infrastructure deficitand climate-proofing all new and existing infrastructure andurban developments. From this can come a better idea of thekind of funding needed for adapting infrastructure to climatechange risks, and from this, some thoughtful discussion ofwhat these imply for adaptation costs and adaptationfunding, in general. It would only take a few such studies ofmajor cities that are particularly at risk from climate changeand have large infrastructure deficits to show that theUNFCCC estimates for Africa and for most cities in Asia arefar too low. It is also likely that studies of major cities in LatinAmerica at high risk from climate change would also showthe UNFCCC estimates for these regions to be far too low.

The UNFCCC notes138 that even with a growingnumber of location-based estimates for costs, it will be diffi-cult to extrapolate these to figures for whole regionsbecause of:

• Very large differences in contexts (risks and vulnerabil-ity), including the scale of the infrastructure deficitsand the extent of the local governance failures. In mostof the locations with the largest infrastructure deficitsand governance failures, much of the data needed toassess such costs are simply not there.

• Very large differences in costs. The estimate in London’sadaptation plan that it can cost UK£15,000 to make asingle dwelling in London cooler in summer could build15 houses in many Asian and African urban centres.

• The ‘moving target’ of urbanization. United Nationsprojections suggest that almost all growth in the world’spopulation in the next few decades is expected to be inurban areas in developing countries.139

• Public costs versus private costs. Many of the costs inadapting cities – particularly in upgrading housing stock– will be borne by private individuals and are even moredifficult to account for. Estimates that are based only onthe costs of adapting infrastructure are thus certainlynot the ‘total costs of adaptation’.140

CHALLENGES TOADAPTATIONMost of the world’s urban population and most of its largestcities are now in developing countries. Furthermore, and asnoted in the introduction to this chapter, most of the growthin the world’s population over the next few decades is likelyto occur in the urban centres of developing countries. At thesame time, most of the urban centres most at risk fromclimate change are in developing countries. And it is inurban areas in developing countries that the deficits in infra-structure and services needed to protect populations fromclimate change are most evident. Yet, most governments andmany international agencies still give little or no attention to


One recent estimatesuggested that thecost of removing thehousing and infrastructuredeficit in developingcountries by 2030would be someUS$6.3 trillion

The UNFCCCestimates for Africaand for most citiesin Asia are far toolow

urban adaptation. Many disaster response agencies are alsobetter equipped to deal with rural disasters than urban disas-ters.141

Perhaps the most pressing challenge for climatechange adaptation in urban areas in developing countries isto get it seen and understood as a central dimension ofdevelopment – and, thus, also a central dimension ofeconomic strength and poverty reduction, including meetingthe Millennium Development Goals. If the MillenniumDevelopment Goals were met in urban areas, it wouldcertainly increase their resilience to climate change. How-ever, this raises a second challenge of how to get far moreeffective local action on the ground for development thatincludes the needed attention to adaptation. A city’seconomic success may be important for its adaptive capacity– but there are many cities with successful economies wherelarge sections of their population still live in informal settle-ments that lack the infrastructure and services that reduceclimate-related (and many other) risks.

It will also be difficult to balance present and futureneeds. The adjustment of building and infrastructurestandards and designs to address likely increases in extremeweather or water constraints – that may not becomeevident for 20 or more years in the future – is important asit will be more expensive to rebuild or adjust these in 10 to20 years. With investment capacity so constrained in mosturban centres in developing countries, however, the extracosts of building resilience to future risks will be contestedby those who claim that there are more pressing priorities.In this context, it will especially be difficult to get theneeded priority to risk reduction for lower-income groups,as wealthier and more powerful interests (residents andbusinesses) want their risks, vulnerabilities and adaptationneeds to be addressed first. City governments that havelong ignored the needs and priorities of those living in infor-mal settlements are not likely to become committed toaddress these deficits.

Effective action on adaptation on the ground alsodepends on a willingness to act by local governments. Thegeneric lessons that can be drawn from the experiences ofcities that have already developed adaptation plans werediscussed above.142 These include building a commitment toact among the different stakeholders, developing the infor-mation base on current conditions (and risks), and develop-ing city-wide risk/vulnerability assessments that draw oncommunity and district assessments. City and municipalgovernments need to consider how to reduce climate-relatedrisks within their plans and investments in infrastructureand land-use management. This usually depends on, or ismuch enhanced by, civil society organizations, especiallythose that represent and work with those who are most atrisk. An earlier section also discussed the key roles for localgovernments and for civil society groups of building orsupporting the building of resilience to climate-relatedstresses and shocks.143 Here, too, there are many co-benefitswith development (and poverty reduction).

However, within each country and urban centre,different stakeholders may be working according to verydifferent worldviews of adaptation. This may hamper efforts

at creating coherent and holistic adaptation responses thattake into consideration the different vulnerabilitieshighlighted earlier in this Global Report.144 There is also thegrowing influence of those who insist that climate change isnot happening or that it will bring few costs; a web-basedconsultation on London’s adaptation programme145 thatasked for comments and suggestions produced manyremarks to this effect that also showed little or no under-standing of climate science.

In addition, little attention is given to urban adapta-tion by most international agencies, even as they discuss anddevelop policies on adaptation.146 Where internationalfunding is available for adaptation, it will be difficult to getthe needed attention for addressing the (often very large)deficits in infrastructure and services (the lack of provisionfor piped water, storm and surface drains, all-weather roads,emergency services, etc.) that arise from governance failuresand limitations because these are not seen as climate changerelated. Getting international support available in a form thatallows it to support effective urban adaptation which isintegrated within local development (and build local adapta-tion capacity) is thus a challenge. There are also all theconstraints faced by international agencies from their lack ofcapacity to support local engagement, as they have shiftedtheir support to sector support and basket funding.147

Channelling funding through recipient governments andsupporting their priorities serves development when thesegovernments are competent, representative and account-able; but this is often not the case. This raises issues aboutthe structures and effectiveness of international agencies insupporting needed local action on climate change in thethousands of urban areas where this is required.

Furthermore, official development assistance was not,in the first place, set up to support local governments andcivil society groups with regard to adaptation efforts. Thereis little clarity as yet on how international funding for adapta-tion (hopefully integrated within development) can workwith and serve local governments and civil society groupswithin each urban centre. The key roles of local governmentand civil society as designers and implementers of climatechange adaptation in urban areas may be better appreciated;but the means by which they can influence climate changenegotiations and institutional responses and hold interna-tional funders of adaptation to account is not yet clear.

It is important to note that the failure to mitigatesufficiently in developed countries will create ever moreadaptation failures, mostly in developing countries, includingmany countries with insignificant historic and current contri-butions to climate change. It is also difficult to see anyagreement reached on needed mitigation strategies by thegovernments of developing countries unless the govern-ments in developed countries demonstrate their commit-ment to mitigation by taking responsibility for their (veryhigh) contribution to global climate change. For (local andnational) governments in countries with minimal per capitaGHG emissions, it is very difficult to justify to theirelectorates expenditures on climate change mitigation ifthey are already unable to provide their populations withbasic infrastructure and services.

Perhaps the mostpressing challengefor climate changeadaptation in urbanareas in developingcountries is to get itseen and understoodas a central dimen-sion of development

City and municipalgovernments needto consider how toreduce climate-related risks withintheir plans andinvestments in infrastructure andland-use management

The failure tomitigate sufficientlyin developedcountries will createever more adaptation failures,mostly in developingcountries, includingmany countries withinsignificant …contributions toclimate change


Most of the urban populations and places at greatestrisk from climate change are not those with large historic orcurrent contributions to GHGs. As noted in Table 1.4, theaverage African (excluding South Africa) individual emitsonly 54 per cent of the CO2 emitted by the average Indian,only 16 per cent of that emitted by the average Chinese, andonly 4 to 8 per cent of that emitted by the average citizen ofthe major developed countries. And, in terms of totalfigures, if CO2 emissions from all African countries (exceptSouth Africa) were cut in half, this would only imply a 1.2per cent reduction in global emissions. In contrast, a similarglobal emissions reduction could be achieved by the USthrough a national reduction of CO2 emissions of only 6 percent. Such issues of environmental justice are playing animportant part in the increasing focus being given to climatechange adaptation in developing countries.

There is also the larger issue for urban adaptation ofpopulation displacement at a national scale and its influenceon migration, including that to urban centres. If citiesbecome the destination of very large flows of rural migrantsdriven from their homes and livelihoods by, for instance, thedamage brought by climate change to agriculture, it will addfurther to the infrastructure deficit and probably to thescale of settlement on hazardous sites. There are predic-tions that by 2050, some 200 million people may be forcedto leave their homes due to environmental degradation andwater shortages caused by climate change.148 Yet, studies ofmigration show how population movements are generallyrational, well-informed responses by individuals and house-holds to changing circumstances. Thus, they are, in fact, akey part of individual and household adaptation. Land degra-dation or decreases in rainfall do not inevitably result inmigration. Or where they do, most movement is short term,as in response to extreme weather disasters, and shortdistance, as in migrant responses to drought and land degra-dation.149

Where there are slow-onset impacts from climatechange (e.g. rising temperatures and declining rainfall), thiscan bring negative impacts upon agriculture; but incomediversification and short-distance circular migration are likelyto be common responses.150 Where climate change iscausing environmental stress for rural livelihoods, it will beone among a number of factors in determining migration. Inaddition, support for agriculture – including agriculturaladaptation initiatives – does not necessarily reduce rural–urban migration. Indeed, successful rural development oftensupports rapid urban development locally as it generatesdemand for goods and services from farmers and ruralhouseholds.151 Yet, a failure by governments and interna-tional agencies to reduce global GHG emissions and tosupport rural and urban populations to adapt will bring crisis-driven population movements that make those forced tomove very vulnerable. Here, migration is no longer plannedmovement helped by knowledge and contacts in the destina-tion area. The pressures on crisis-driven populationmovements will also be much increased if developedcountries fail to agree on implementing the large reductionsin GHG emissions that are needed to avoid dangerousclimate change.

So far, there is debate as to whether climate changehas yet led to forced migration from any location.152 Yet,there is growing concern about how to address the issue ofmigrants who are forced to leave their homes due to futureclimate change. This aspect of ‘residual damage’, peoplewhose lives and homes cannot be adapted in situ, fallsoutside the scope of most national and international legisla-tion. Under current international law, strictly speaking,those fleeing from environmental pressures are not consid-ered as refugees – this term is reserved for those ‘beingpersecuted for reasons of race, religion, nationality, member-ship of a particular social group, or political opinion’.Furthermore, the term ‘refugee’ refers only to people whoare ‘outside the country of [their] nationality’.153 In interna-tional law, people who are displaced within their owncountry are referred to as ‘internally displaced persons’.Thus:

… there is a broad consensus among lawyersconsidering the issue of climate change migra-tion that current protections at internationallaw do not adequately provide for a number ofthe categories of person likely to be displaced byclimate change.154

There are major consequences of this inadequate protectionin human rights law – namely, who will be responsible forassisting this group? If international climate migrants wereto be considered refugees, this would imply a responsibilityof countries to offer them the same protection as they offerto political refugees. So far, not one country has been willingto accept such a definition.155 At the same time, the interna-tional agency with the primary responsibility for dealing withrefugees, and which has been taking on the task of address-ing the concerns of internally displaced persons as well – theOffice of the High Commissioner for Refugees – is ‘alreadyoverstretched and … unable to cope with their current“stock” of refugees’.156 Thus:

Given the nature and magnitude of the problemwhich climate change displacement presents,ad hoc measures based on existing domesticregimes are likely to lead to inconsistency,confusion and conflict.157

There are thus increasing calls for the development of newinternational legislation to address the concerns of ‘climatemigrants’ – perhaps in the form of an international conven-tion for persons displaced by climate change.158

CONCLUDING REMARKSAND LESSONS FOR POLICYWhat needs to be done to support the adaptation of urbanareas to climate change has become clearer during the lastten years, in large part because of innovations by civil societygroups and local governments, some of which have beendescribed in this chapter. What is much less clear is how to

If cities become thedestination of verylarge flows of ruralmigrants drivenfrom their homes …by … climate change…, it will addfurther to the infrastructuredeficit and probablyto the scale of settlement onhazardous sites

The pressures oncrisis-driven populationmovements will …[increased] if developed countriesfail to agree onimplementing …large reductions inGHG emissions

There are …increasing calls for… new internationallegislation toaddress theconcerns of ‘climatemigrants’ – perhapsin the form of aninternationalconvention


A focus on community-basedadaptation, localassessments or theinternational transfer of fundsonly is unlikely to bea successful recipefor climate changeadaptation at thecity level

It is … importantthat the emergingknowledge aboutclimate changeadaptation in urbanareas is synthesizedand included in theFifth AssessmentReport of the IPCC

translate ‘what needs to be done’ into ‘how to do it’,especially in countries and urban areas with weak localgovernments or local governments unwilling to work withthe low-income groups within their jurisdiction.

Clearly, one important way forward is to work withand learn from the innovators – in grassroots organizations,in local governments, in national governments and in inter-national agencies. Another is to encourage the engagementof all key stakeholders in cities (which in the end meansalmost everyone). This includes far more attention to theneeds and capacities of those who are most at risk fromclimate change. Here, consultations on the ground and riskassessments are not focused on ‘climate change’, but on allthe risks and vulnerabilities that they face – some, most orall of which are likely to be exacerbated by climate change.This can be the basis for risk and vulnerability assessmentsthat inform a ‘climate change aware’ development agenda.This has to build resilience both to the specific threatsidentified as certain or likely from climate change and, moregenerally, to all the stresses and shocks that threaten thewell-being and livelihoods of low-income groups. Anotherimportant issue here is how to make the adaptationmeasures provided or financed by the private sector thatserve better-off households and businesses extend theirrange so that they also serve smaller businesses and lower-income households.

Yet, it has to be kept in mind that a focus on commu-nity-based adaptation, local assessments or the internationaltransfer of funds only is unlikely to be a successful recipe forclimate change adaptation at the city level. Successfuladaptation also has to take into account the following majorissues:

• Concerted action at the household, community, localgovernment, national government and internationallevels are required.

• Global and national projections about climate changeimpacts have to be improved in order to better supportmeasures at the local level. At present, projections areinsufficiently precise or, at times, contradictory, whichimpedes local action.

• The issue of social and environmental justice needs toget appropriate attention, both within cities andcountries, but also internationally. As is acknowledgedby the UNFCCC, the bulk of funding for climate change

adaptation has to come from those countries that areresponsible for global climate change. Also, there is aneed to consider who is to pay for the homes andproperties lost from the impacts of climate change thatcannot be adapted to: the so-called ‘residual damage’.

• The emerging international funding for climate changeadaptation has to be adequate to the task at hand, andshould explicitly allocate a fair share of resources tourban settlements. At present, resources are inadequateand do not target urban settlements.

It is also important that the emerging knowledge aboutclimate change adaptation in urban areas is synthesized andincluded in the Fifth Assessment Report of the IPCC that willbe developed between 2010 and 2014. The work under-taken in preparing this Global Report, as well as otherUN-Habitat activities, is already feeding into that process.The Fourth Assessment Report of the IPCC, published in2007, focused on reviewing and summarizing the evidencefor human-induced climate change and presenting the casefor the importance of action both on adaptation and mitiga-tion. The Fifth Assessment Report needs to go much furtherin summarizing and synthesizing what is known about howto achieve adaptation (and mitigation). The initial work forIPCC’s Fifth Assessment recognizes the need for more atten-tion to human settlements; in the plans for the FifthAssessment Report, the Working Group II on ‘impacts,adaptation and vulnerability’ includes three chapters on‘human settlements, industry and infrastructure’, comparedto only one in the Fourth Assessment. This includes achapter on urban areas, another on rural settlements and athird on networked infrastructure that serves all humansettlements (including transport, energy and water).159

There are also measures under way to have closer linksbetween the various working groups on the role of cities andother settlements in considering both adaptation and mitiga-tion; here the interest is in the co-benefits betweenadaptation and mitigation. It is also being planned that theFifth Assessment Report should have more detailed coverageon human health, security and livelihoods, and poverty. Theongoing work of the IPCC will thus serve to get the attentionof national governments and international agencies to all themeasures needed to address climate change adaptation inurban areas discussed in this chapter.

1 Satterthwaite, 2007.2 UN, 2010. See also Chapter 1.3 The definitions used in this

section are based on Parry et al(2007b). See also Box 1.1.

4 See Chapter 1 and also UN-Habitat (2007) for an in-depthdiscussion of resilience withrespect to natural and human-made disasters.

5 See also discussion of vulnera-bility in Chapter 4.

6 See Chapter 5.7 See Chapter 1.8 Mitlin, 2008.

9 See section on ‘Household andcommunity responses to theimpacts of climate change’.

10 Bicknell et al, 2009.11 See Chapter 4.12 See Wisner et al, 2004.13 See Chapter 4 for a more in-

depth discussion ofvulnerability.

14 Stephens et al, 1996.15 Mrs Fatu Turay, Kroo Bay

Community, Freetown, SierraLeone. ActionAid International,2006, p6.

16 Douglas et al, 2008.

17 ActionAid International, 2006, p4.18 Dodman et al, 2010b.19 Jones and Rahman, 2007.20 Mitlin and Dodman, forthcom-

ing.21 Boonyabancha, 2005, 2009.22 Hasan, 2006, 2010.23 This example is drawn from

López-Marrero and Tschakert,forthcoming.

24 Similar differences in percep-tion of risks and impacts havebeen noted in Delhi, India(Diana Reckien, pers comm,2010).

25 Wamsler, 2007.26 Mitlin and Dodman, forthcom-

ing; see also Banks, 2008.27 Sabates-Wheeler et al, 2008.28 Prowse and Scott, 2008.29 Dodman and Satterthwaite,

2008.30 Moser and Satterthwaite, 2008.31 See Roberts, 2008.32 Karol and Suarez, 2007;

Roberts, 2010a; .33 Stern, 2006; Satterthwaite et al,

2007a.34 Satterthwaite et al, 2007a.35 See Chapter 2.


NOTES

36 Satterthwaite et al, 2009a.37 Dalal-Clayton, 2003.38 Satterthwaite et al, 2007a;

Satterthwaite et al, 2009a.39 Huq et al, 2003.40 The City of Durban has been a

pioneer within Africa in devel-oping a coherent inter-sectoraladaptation strategy. SeeRoberts (2008, 2010a) for anaccount of the difficulties ingetting buy-in from withindifferent sectors in govern-ment. See also the sectionbelow on ‘Moving from riskassessments to adaptationstrategies’.

41 This section draws on Hintz,2009.

42 Pelling, 1997.43 This section draws on Bangkok

Metropolitan Administration,2009.

44 Roy, 2009.45 It should be noted that many

of the actions implemented inBangladesh, particularly duringthe early years, were address-ing natural disaster risks, ratherthan climate change adaptationper se.

46 Alam and Rabbani, 2007.47 The section on Durban draws

on Roberts (2008, 2010a,2010b); the section on CapeTown draws on Mukheibir andZiervogel (2007).

48 Roberts, 2008, 2010a.49 UN, 2010.50 Roberts and Diederichs, 2002a,

2002b.51 The discussion on Durban

draws on Roberts, 2008,2010a; and Debra Roberts,eThekwini Municipality,Durban, South Africa, perscomm, September 2009.

52 Roberts, 2010a.53 See www.durban.gov.za/

durban/services/epcpd/about/branches/climate-protection-branch.

54 Roberts, 2010b.55 Roberts, 2010b.56 City of Cape Town, undated.57 Departments such as roads

and storm water, disaster riskmanagement and housing (Cityof Cape Town, 2010).

58 In practical terms, this may bebetter understood as thesecond step, as it first needsthe decision by the citygovernment to think aboutclimate change adaptation, andthen to commission the workneeded to advance such think-ing.

59 Nickson, 2010.60 This draws on City of

Melbourne, 2009.61 This draws on City of

Rotterdam, 2009 and undated.62 This draws on IFRC, 2010,

especially Chapter 7.

63 See, for instance, UN, 2009;IFRC, 2010.

64 Lungo, 2007.65 Gavidia, 2006.66 Adger et al, 2007. 67 Note the literature on the

early adopters. See, forinstance, Carmin et al (2009).

68 Satterthwaite et al, 2007a.69 Boonyabancha, 2005;

Usavagovitwong andPosriprasert, 2006; Some et al,2009; see also Hasan, 2006.

70 van Horen, 2001; Torres et al,2007.

71 Syukrizal et al, 2009.72 See Roberts, 2008, 2010a.73 UN, 2009.74 See the above section on

‘Community responses‘.75 Osbahr and Roberts, 2007;

Kehew, 2009.76 See discussion earlier in this

chapter.77 See Roberts, 2010a, for a

discussion of this in relation toDurban, South Africa.

78 For a more elaborate discus-sion on urban planning, seeUN-Habitat, 2009a.

79 See ADB, 2005.80 Satterthwaite et al, 2007a.81 Revi, 2008.82 See Hintz, 2009, and the above

section on ‘Local governmentresponses to the impacts ofclimate change’.

83 World Bank, 2008.84 World Bank, 2008.85 Bizikova et al, 2008.86 World Bank, 2008.87 See the section below on

‘Challenges to adaptation’88 Parry et al, 2007b, p880. See

also Box 1.1 and the discussionof resilience in UN-Habitat,2007.

89 See Chapter 2.90 See discussion in López-

Marrero and Tschakert,forthcoming.

91 Parry et al, 2007b, p880.92 Dodman et al, 2009.93 Stern, 2009.94 See www.unhabitat.org/

categories.asp?catid=634, lastaccessed 14 October 2010.

95 See www.citiesalliance.org/ca/cds, last accessed 14October 2010. It should benoted that the CityDevelopment Strategiesapproach does not yet clearlyaddress climate change per se.

96 Pieterse, 2008.97 See discussion in the section

on ‘Household and communityresponses to the impacts ofclimate change’ above.

98 Hasan, 2010.99 Satterthwaite et al, 2007a.100 Such as Durban (South Africa)

and Manizales (Colombia).101 See section on ‘Local govern-

ment responses in developing

countries’ above.102 Velasquez, 1998.103 Díaz Palacios and Miranda,

2005.104 Carmin and Zhang, 2009.105 See Cabannes, 2004.106 See, for instance, Menegat,

2002.107 Pelling et al, 2008.108 Tanner et al, 2009.109 Manuel-Navarrete et al, 2008.110 Satterthwaite et al, 2009a.111 See also Roberts, 2010a.112 Cohen and Garrett, 2010.113 See Maxwell et al, 1998; Cohen

and Garrett, 2010; Tolossa,2010.

114 This section draws on UN-Habitat, 2008a, and the Citiesand Climate Change Initiative’swebsite at www.unhabitat.org/content.asp?typeid=19&catid=570&cid=6003, last accessed14 October 2010.

115 Additional cities are joining theinitiative in Africa, Asia andLatin America.

116 See the section on ‘The poten-tial of the international climatechange framework for localaction’ in Chapter 2.

117 It should be noted that theAdaptation Fund becameoperational in 2010; see Box2.2.

118 UNFCCC, 2010.119 Ayers, 2009.120 Ayers, 2009.121 As can be seen from Table 1.4,

developed countries and thetop nine GHG-emitting devel-oping countries areresponsible for 83 per cent ofall GHG emissions (in 2005)and 87 per cent of all CO2emission (in 2007).

122 See section on ‘Challenges toadaptation’ below.

123 See UN, 2009; IFRC, 2010.124 UN, 2009.125 Dodman and Satterthwaite,

2009.126 For more details, see IFRC,

2010.127 Parry et al, 2009.128 Hardoy et al, 2001.129 UN-Habitat, 2010, p42.130 Disasters included in the

Emergency Events Database,CRED, Louvain, Belgium(www.emdat.be).

131 UNFCCC, 2007, para 371, p90.132 This having been said, however,

it is easy to argue that manyparts of the infrastructuredeficit are only marginallyrelated to the adaptive capacityof a community. The adaptivecapacity of New Orleansduring Hurricane Katrina in2005, for example, would nothave been much different if, say,20 or 80 per cent of thepopulation had access tosewerage services or piped

water. Yet, in terms of urbangovernance, it is hard for localgovernments, particularly indeveloping countries, to justifyinvestments in ‘pure’ climatechange adaptation measures ifa large proportion of thepopulation do not have accessto basic infrastructure and/orservices.

133 Dodman and Satterthwaite,2009.

134 Parry et al, 2009.135 UN Millennium Project, 2005.136 Parry et al, 2009.137 UN, 2009.138 Dodman and Satterthwaite,

2009.139 UN, 2010.140 Dodman and Satterthwaite,

2009.141 Suarez et al, 2008; IFRC, 2010.142 See the section on ‘Generic

lessons for city governments’above.

143 See the section on ‘Buildingresilience’ above.

144 See Chapter 4.145 See www.london.gov.uk/

climatechange, last accessed 14 October 2010.

146 See, for instance, the lack ofattention to this in the recentHuman Development Report onthe topic of climate change(UNDP, 2007).

147 Crespin, 2006. ‘Basket fundingis the joint funding by anumber of donors of a set ofactivities through a commonaccount, which keeps thebasket resources separatefrom all other resourcesintended for the samepurpose’ (Ministry of ForeignAffairs of Denmark, 2006, p2).

148 See note 257 in Chapter 4.149 See Henry et al, 2004; Massey

et al, 2007; Tacoli, 2009.150 Tacoli, 2009.151 See Beauchemin and Bocquier,

2004; Henry et al, 2004; Masseyet al, 2007.

152 See, for example, Brown, 2007.153 Convention relating to the

Status of Refugees, Article 1,http://www2.ohchr.org/english/law/pdf/refugees.pdf, lastaccessed 13 October 2010.

154 Hodgkinson et al, undated.155 Brown, 2007.156 Brown, 2007, p8.157 See www.ccdpconvention.com/

documents/CCDPConventionFAQs.pdf, p3, last accessed 13 October 2010.

158 See www.ccdpconvention.com,last accessed 13 October2010.

159 See www.ipcc.ch/activities/activities.htm for more details,last accessed 18 October2010.


If concerted action is not undertaken to reduce greenhousegases (GHGs) and promote more environmentally sustain-able and equitable patterns of urban development, there willbe a deadly collision between urbanization and climatechange. The dangerous course to this collision threatens tohave unprecedented negative impacts upon human develop-ment, quality of life, economic production, political stabilityand the health and resilience of the ecosystems upon whichhuman beings depend. However, the coming together ofurbanization and climate change will also offer an unprece-dented opportunity. Urban areas, with their high concent-rations of population, buildings, industries and infrastruc-ture, will face the most severe impacts of climate change.Yet, the same urban areas can become hubs of innovationwhere alternative options can be designed and tested topromote reductions in GHG emissions (mitigation) andvulnerability to climate change impacts (adaptation).

Significant linkages exist between climate change anddevelopment. While climate change is jeopardizing develop-ment goals, mitigation and adaptation targets could begreatly threatened by unsustainable pathways of develop-ment. Climate change cannot be addressed effectively unlessmore effective actions are undertaken to reduce emissions,cope with climate changes already under way, and create theconditions to enhance the adaptive capacity of poorcountries and population sectors (environmental justice).Mitigation efforts need to focus not only on reducing carbonintensity, or increasing the energy efficiency of infrastruc-ture, buildings, and economic and domestic activities, butalso on reducing both the total consumption of fossil fuelsand emissions of GHGs through other means. Adaptationstrategies cannot be reduced to redesigning buildings andinfrastructure, but will also require use of local knowledge,greater participation of key stakeholders, and higher institu-tional capacity of local governments. In many developingcountries, urban centres lack all-weather roads, good-qualityhomes and other preconditions for successful adaptation(i.e. they suffer from an ‘adaptation deficit’). It is thereforenecessary to relate adaptation and mitigation responses todevelopment and foster sustainable development withmitigation and adaptation strategies in mind.

Equity is a fundamental dimension of the relationshipbetween climate and development. Because of uneven devel-

opment patterns and distribution of wealth and infrastruc-ture services at global, national and urban levels, withindifferent sectors, and between different individuals, there isoften an inverse relationship between responsibility forclimate change and suffering of its consequences. Thelargest national emitters of GHGs are, by far, the developedcountries and a few rapidly industrializing developingcountries (see Table 1.4), and this trend can also be seen,generally speaking, in the wealthy sectors within countriesand cities around the world. Yet, climate change will deal itsheaviest blows on those contributing the least to GHGemissions: poor countries and the poor and vulnerablewithin their societies.

There are, at present, many actions at different levelsdesigned to respond to the daunting challenge of climatechange. Nearly all national governments have signed theUnited Nations Framework Convention on Climate Change(UNFCCC) and dozens have launched responses at thenational level. Numerous provincial/state and local authoritieshave promoted vigorous, yet varied responses to addressclimate change, even in the absence of incentives fromnational governments. Many local authorities are also under-taking a range of mitigation and adaptation measures.Notwithstanding all of these, climate change remains, inpractice, a marginal issue for most decision-makers. ThisGlobal Report has explored the reasons for this, as well aswindows of opportunity that can be used or created to helpurban populations and decision-makers reduce their emissionsand adapt to climate change in ways that promote sustainable,equitable and resilient paths of urban development.

The purpose of this chapter is to provide an overviewof the key findings and messages from all chapters of theGlobal Report. It will briefly revisit the constraints,challenges and opportunities to mitigation and adaptationactions, and point to some of the linkages among drivers andvulnerabilities. Drawing further from the findings of theprevious chapters, this concluding chapter reflects on themultiple linkages, synergies and trade-offs between mitiga-tion, adaptation and urban development. The chapter endswith a set of suggestions on future policy directions, focus-ing on local, national and international principles andpolicies for supporting and enhancing urban responses toclimate change.

If concerted actionis not undertaken toreduce … GHGs …there will be adeadly collisionbetween urbanization andclimate change

There is often aninverse relationshipbetween responsibility forclimate change andsuffering of itsconsequences

C H A P T E R

CONCLUSION AND POLICYDIRECTIONS

7

KEY FINDINGS AND THEIRIMPLICATIONSUrbanization and climate change are two human-inducedforces that have put humanity at a crossroad of at least twofuture directions that this Global Report has explored. First,there is the plausible future of continuation along a danger-ous collision course if national, regional and localgovernments continue with business as usual. Many of thedysfunctions of the current political, economic and socialsystems at play could lead inexorably to the very worstoutcomes imaginable. For example, it has been difficult forthe developed countries, which bear the main responsibilityfor current GHG emissions,1 to achieve effective mitigationtargets. Notwithstanding decades of development policies,the story of how affluence and poverty affect global climatechange is still a tale of two development paths explainingdiverse levels of emissions within and across cities. Thisdifference also creates common but differentiated mitigationand adaptation responsibilities (i.e. the wealthy should bemost responsible for mitigation and adaptation responses).However, the political reality is that the wealthy also have agreater influence on the political structures at play, makingsuch equitable distribution of responsibility difficult at best.Furthermore, uneven development and inadequate infra-structure and governance structures constrain the ability ofpopulations and local authorities of many urban centres toadapt to existing and future climate change and to otherenvironmental and societal stresses.

A second plausible future, and the only option forhumanity to avoid the first, is one for which cities havehistorically proved their talents as sources of innovation, andlaboratories for the transition to different and more sustain-able (i.e. less carbon intensive and more resilient) pathwaysof development. The findings of this Global Report, brieflysummarized, contribute to making this second option possi-ble.

Main issues of concern

Trends of urban change in recent decades have a strongbearing upon the present report. Urban population growthhas taken place at an unprecedented rate, with a nearquintupling of total urban populations between 1950 and2011. During the same period, the urban population hasincreased from being less than one third (28.8 per cent in1950) to more than one half of the global population (50.8per cent in 2011). The fastest rates of urbanization arecurrently taking place in developing countries, with the bulkof this growth taking place in smaller urban areas.2 This,coupled with the increased intensity and frequency ofadverse weather events, will have devastating effectsprecisely where the capacity to deal with the consequencesof climate change is weaker, or even lacking. Smaller urbancentres in developing countries are often institutionallyweak, and unable to promote effective mitigation andadaptation actions. At the same time, a possible advantagealso exists as the burgeoning development of these centresmay be redirected in ways that reduce their emission levels

to a desired minimum – for example, through the promotionof mono-centric urban structures based on the use of publictransportation. Their resilience and ability to cope withclimate hazards and other stresses may also be enhanced –for instance, through the development of climate-proofurban infrastructures and effective response systems.

This Global Report aims at contributing to an under-standing of the drivers of GHG emissions from urban areas.The purpose of developing this understanding is to helpurban policy-makers, enterprises and consumers target effec-tive options for reducing these emissions at the same timethat they enhance urban resilience to the impacts of climatechange. Last, but certainly not least in importance, thedynamics of urban centres are intimately linked not only tothe role of geography in determining a city’s need for energyto run heating and air-conditioning systems, or to get accessto sources of energy, but also to the role that geography playsin giving cities access to biodiversity, clean water and otherecosystem services at risk from the impacts of climatechange. Furthermore, since urban areas have developed overexisting ecosystems (or ‘ecozones’) such as coastal areas,wetlands, drylands, etc., intimately linked to geography andto ecosystem services threatened by changes in the climatesystem, policies aimed at mitigation and adaptation in theseareas should also consider protection or enhancement ofnatural systems – for example, through tree-planting andcoral reef restoration.

Climate change is also interacting with urbanizationand, in doing so, increases the magnitude of the develop-mental and environmental challenges and threats that urbangovernments are already facing as a result of the pace ofcurrent urbanization (each year sees the addition of 67million new urban dwellers, 91 per cent of whom are addedto cities in developing countries).3 The most recent empiri-cal evidence points unequivocally to the conclusion that theEarth’s climate is warming and that this warming has beeninduced by the massive amounts of GHGs that human beingshave pushed into the atmosphere. Human-induced changesin the climate system have been further validated byresearch that has been published after the release of theFourth Assessment Report of the Intergovernmental Panel onClimate Change (IPCC) in 2007. According to this assess-ment, the observed increase in global mean surfacetemperature since 1990 is 0.33°C. At the same time,changes have been documented in the frequency and sever-ity of storms, precipitation, droughts and other weatherextremes of relevance for urban centres.

The main human sources of GHGs are the dramaticrise in energy use, land-use changes and emissions fromindustrial activities. Increases in GHG emissions have been,to a limited extent, offset by increases in efficiency and/or reductions in the carbon intensity of production andconsumption. However, the overall global trend has stillbeen towards large increases in the total amount of anthropogenic (or human-caused) GHG emissions.

Since the onset of the industrial era, urban centreshave played a key, though not yet fully understood, role inthe unprecedented increases of carbon dioxide (CO2) andmethane emissions. Furthermore, emissions are now

Climate change …increases the magnitude of thedevelopmental andenvironmentalchallenges andthreats that urbangovernments arealready facing

The main humansources of GHGs arethe dramatic rise inenergy use, land-usechanges andemissions fromindustrial activities


increasing above the worst scenario established by the IPCC.In this context, humanity is facing two main challenges thaturban centres can help address: the need to adapt, at least tosome amount of continued warming already under way, andthe need to mitigate (i.e. to achieve development paths thatbring about a peaking of emissions by 2015 and a stabiliza-tion of GHG concentrations).

While industrialization is certainly responsible for therapid pace of global climate change, and urbanization isstrongly related to industrialization, two questions ofprimary importance are still being addressed (i.e. theamount of GHG emissions that urban areas are actuallyresponsible for, and the linkages among levels of urbaniza-tion, economic development and emissions). Chapter 3showed that, because of the complexities involved in calcu-lating the urban contribution to GHG emissions and the lackof agreement by researchers on exactly what items toinclude in the inventories, no precise figures exist of howhigh a contribution to global warming cities make. Earlierchapters have also illustrated how a dynamic, complex andstrong link exists between economic development, urbaniza-tion and GHG emissions. However, this relationship is in noway straightforward. Differences in GHG emissions resultfrom the peculiarities and weight of different emittingsectors (such as industries, buildings and transportation).Diverse factors account for the different levels and sourcesof urban GHG emissions both within and across countries.These include:

• differences in how energy generation, transportationand other emitters operate;

• levels of economic development and affluence asmeasured by gross domestic product (GDP) per capita;

• technology and technological innovations and acquisi-tion;

• geographic factors;• demographic structure and dynamics of a city;• urban functions and a city’s economic base;• urban form (spatial structure) and, related to it, the

layout and structure of a city’s transportation system;• city size (i.e. the ‘agglomeration’ effect);• climate conditions and natural endowments; and• market prices and the wider institutional setting of the

city and of the broader – national and international –governance structure within which it operates.

The inverse relationship between being the most at fault forthe causes of climate change and suffering its most profoundconsequences springs directly from historical and existingpatterns of inequity in development, distribution of wealth,lifestyle and availability of infrastructure services. Thisinequity exists not only at the global level, where developedcountries and a few rapidly industrializing developingcountries are the main contributors to total CO2 emissions.It also occurs at the national and local levels, creating differ-entials in contribution to GHG emissions along severaldifferent economic and social lines. These differences can befound within and across cities, between the rich and thepoor, the racial or ethnic minority and the majority, the old

and the young, and between men and women. This follows,in general, the differential access to resources, services andpolitical power among and between these groups. As such –even within developing countries – it is the affluent andpolitically enfranchised enclaves, groups and communitieswith access to more services and amenities who consumemore, travel more and become the highest GHG emitterswithin their cities, regions and countries. This deeplyentrenched inequity lies at the heart of environmentaljustice issues surrounding climate change mitigation andadaptation actions.

The concentration, within urban centres, of peopleand their homes, infrastructure, industries and waste withina relatively small area can have two implications for policiesaimed at avoiding the negative urban impacts of climatechange. On the one hand, urban areas can be dangerousplaces in which to live and work; their populations can bevery vulnerable to extreme weather events or other hazards,with the potential to become disasters. Furthermore, urbansettlements can increase the risk of ‘concatenated hazards’.Industrialization, inadequate planning and poor design canbe key determinants of secondary or technological risks.

On the other hand, the same concentration of people,infrastructure and economic activities in urban centres alsomeans economies of scale or proximity for many of themeasures that reduce risks from extreme weather events.Policies on enhancing sustainability and on transition fromdisaster response to disaster preparedness can help urbansettlements to increase their effectiveness at coping withclimate hazards.

Not all demographic segments of the urban popula-tion are equally affected by the hazards that climate changeis predicted to aggravate. The capacity of different urbanpopulations to cope or adapt is influenced not only by ageand gender, but also by the context-specific combination offactors such as:

• labour, education, health and the nutrition of theindividuals (human capital);

• the financial resources available to people (financialcapital);

• the extent and quality of infrastructure, equipment andservices (physical capital);

• stocks of environmental productive assets, such as soil,land and atmosphere (natural capital);

• the quality and inclusiveness of governance structuresand community organizations that provide or managesafety nets and other short- and longer-term responses(social capital).

Urban vulnerability to climate change is a dynamic process in many ways: climate change and other stresses – includingmarket integration, governmental policies and environ-mental change – constantly change, as do the dimensionsdefining sensitivity and capacity to adapt. Adaptation is also aprocess of constant adjustments and learning that mayevolve in response to different exposures and past experi-ences. In this context, high adaptive capacity and successfuladaptation to one stress (e.g. drought) may result in

A dynamic, complexand strong linkexists betweeneconomic development, urbanization andGHG emissions

It is the affluent and politically enfranchised …groups and communities …whoconsume more,travel more andbecome the highestGHG emitters

165Conclusion and Policy Directions

exposure to new stresses (such as the urban heat-islandeffect or water scarcity), some of them provoked by copingresponses (such as the use of air conditioning or increasedextraction of groundwater). It is therefore important fordecision-makers to understand how such complex processesinteract and change over time because this understandingcan help to inform more successful adaptation and avoidpotential negative feedbacks or unintended consequences.

Cities and the multifaceted nature of climate responses

Representatives from different countries, states and citiesare responding at multiple sectoral and governmental levelsto the mitigation and adaptation challenges posed by theimplications of climate change. These responses go beyondtraditional national and state activity, and frequently imply not only multilevel public interventions, but alsopublic–private cooperation and autonomous responses, andself-regulation by individuals and groups. These responsesand the issues that they are intended to address are multi-scale in nature because most of the processes involvedoperate at multiple levels. It is frequently the case thatmitigation and adaptation responses do not fit with theissues that they are intended to address. For instance, manyof the climatic cause-and-effect relationships are long termand potentially irreversible and, therefore, require preplan-ning that goes beyond the tenure, administrative power andeven the lifetime of most current decision-makers and stake-holders. This makes policy decisions in this area particularlydifficult, as uncertainties exist in the understanding of theoutcomes and impacts of climate change.

Ideas and policies centred on development, sustain-ability, climate change and some of their central issues(poverty reduction, disaster management and climate changeadaptation) share key characteristics. For instance, in thearea of climate change, the notion of development opens thepossibility of promoting deep transformations in models ofproduction and lifestyles. The specific nature of thesechanges has been defined in different ways. The first anddominant way is to use new markets to manipulate theinputs and outputs of the existing market system in anattempt to transform them, thus affecting everythingbeneath the overarching economic system in a cascading ordomino-like fashion (such as by using carbon markets tocreate incentives to curb GHG emissions). The second wayfocuses first on equity and attempts to create transitionsbased on models of development that include sustainableuse of the environment and non-market-driven alternativesto promote human well-being. It is this vision of sustainableand resilient development that has great potential for amovement away from current, unfair and unsustainablepatterns of energy use and their dangerous impacts upon theclimate system. This alternative model of developmentwould allow urban populations and decision-makers to movetowards equity, minimizing human suffering from climate-related disasters and promoting well-being, while creatingthe conditions for improvements in quality of life forundeveloped areas, including poor urban slum dwellers of

the world. It would create the basis for many alternativedevelopment policies and programmes at the international,national, state (or province) and urban levels of governanceand in civil society. It would also foster development that canfulfil the twin roles of improving the quality of life of theurban poor, while creating sustainable urban lifestyles thatare central to the messages of this report.

Chapter 2 describes the process by which climatechange has become part of the international agenda, explor-ing the main mechanisms, instruments and financingstrategies of the UNFCCC and the Kyoto Protocol. Themessage of climate change, however, only caught publicattention with increased scientific knowledge of, and publicconcern about, global environmental issues that crystallizedin the creation of the UNFCCC. This new public awarenesswas further catalysed by an array of extreme events that areincreasingly affecting the world, and the creation of theIPCC. The chapter also identifies the key actors, componentsand actions of climate governance other than the Climateconvention and protocol at the international, regional,national and sub-national levels. The implications of theinternational climate change milieu for local action at thecity level are described and the extent to which actors of thislevel have benefited from the various funding and supportmechanisms currently available is reviewed.

Chapter 2 also outlines some common features thathave defined the international climate regime, such as theuse of a ‘framework’ scheme with general formulations thatare deliberately ambiguous in order to limit conflictsbetween the positions of all representatives. The basicprinciples arrived at are then fleshed out through regularpost-agreement meetings of the countries that have adop-ted the UNFCCC. Particularly in negotiations during keysessions of the Conference of the Parties (COP) to theUNFCCC, little progress is made during most of the negotia-tion period. Precisely because effective policies to reduceGHG emissions imply deep transformation in energysystems, lifestyles and economic activities, an under-standably high contentiousness exists every time the COPdiscusses how much needs to be mitigated by whom, whenand where (burden and timetables of commitments); whowill pay for the responses and how (financial assistance andtechnology transfer); and what institutions and implementa-tion mechanisms need to be in place to ensure participationand compliance.

Conflicts and uncertainties can help to understand, atleast partially, the complex and fragmented governance ofclimate issues. Yet, equally important is to be aware of thefact that rather than being a wholly rational process, policy-making is an incremental undertaking. Climate governanceis made up of a patchwork of binding agreements (e.g. theKyoto Protocol), organizations (such as the UNFCCC secre-tariat, the IPCC and the United Nations) and networks thatare quite different and distinct in their functions andapproaches (e.g. rule-setting and information-sharing), theirconstituencies (private and public), their spatial scope (local,bilateral to global), their focus (e.g. mitigation, adaptation,disaster management and development), and their capacityto steer climate-relevant action. The Climate Convention

Countries, statesand cities areresponding at multiple sectoraland governmentallevels to the mitigation andadaptationchallenges


More urban authorities than evercurrently participatein transnationalnetworks, research-sharing,learning initiativesand advocacy efforts

Individual andorganizationalleadership has been… shaping climateaction and creatingwindows of opportunity


also coexists with a set of parallel initiatives and frameworks(e.g. the Hyogo Framework), operating at different sectoraland spatial levels and exerting deep influence on climateissues. For instance, the adaptation and disaster risk manage-ment communities share many commonalities, and can learnand benefit from each other’s concepts and experience. Yet,outstanding differences also exist, particularly in terms ofterminology, actors involved and types of intervention.

A relatively small number of countries, states/provinces and cities have played leading roles in addressingmitigation and – to a lesser extent – adaptation. Some (e.g.London, UK; California, US; King County, Oregon, US;Durban, South Africa) have launched ambitious climatechange programmes; have created positive synergies withother tiers of government; and have mobilized the necessarysupport from the public and private sectors to curb GHGemissions and adapt to climate change. However, even theleaders and frontrunners in climate change action are facedwith multiple challenges and difficulties in achieving theirmitigation targets (such as the UK). This is true becausemany proposed actions are voluntary, and policies in many ofthe existing plans do not appear adequate to address theproblem.

Although existing knowledge lags behind the recentexplosion in city responses to climate change, it can be saidthat some urban actors have been able to take advantage ofthe opportunities offered by the multilevel governance struc-tures briefly described in Chapter 2. More urban authoritiesthan ever currently participate in transnational networks,research-sharing, learning initiatives and advocacy efforts.These urban actors have developed a more aggressiveapproach, seeking to secure the economic competitivenessof their cities and to input a local voice in internationalnegotiations (such as the World Mayors Council on ClimateChange at the COPs) and organizations.

Climate action at the urban level has been shaped by amyriad of factors. These are given by institutional conditionsand incentives, such as existing international instrumentsand financing mechanisms, supra-regional programmes andnational regulation systems. This Global Report has provideddifferent examples of this. The emphasis on mitigationstrategies and actions by city-relevant local authorities can bepartially attributed to the importance of such internationalmechanisms and programmes as the Clean DevelopmentMechanism (CDM), which were made operational earlierthan adaptation funding mechanisms, such as the AdaptationFund.4 This mitigation emphasis is also the result of thedesign, within the European Union, of the EuropeanEmissions Trading Scheme – the largest multinational GHGemissions trading scheme in the world – and the leadershipof such countries as the UK, Germany and Norway that havebeen key promoters of climate policies aimed at mitigation.These countries have assembled an array of policies toachieve long-term reductions.

Action on climate change issues – for mitigation oradaptation – is largely a function of knowledge, whethergenerated by scientific communities or brokered by themedia, scientific entrepreneurs or non-governmental organi-zations (NGOs) at different levels (from the international to

the local). It is, hence, necessary for academic institutions,local authorities and key stakeholders to generate the neces-sary information and create the sense of identity and thebuy-in necessary to affect change. Equally important,however, has been the power that different groups have tomake their points of view prevail.

Individual and organizational leadership has beenanother factor shaping climate action and creating windowsof opportunity offered by transnational networks. However,administrative structures, party politics, political timetables,inertias and many other institutional constraints need to beovercome, thus requiring a broader-based institutional capacity for climate protection. The absence of this institu-tional capacity has deterred key mitigation and adaptationefforts. Yet, paradoxically, in some cases (e.g. US actions atthe state and urban levels), it has become another source ofopportunity for state and local actors to fill a leadership gap.

A fundamental goal of urban actors has been to offerthe conditions for business and investment to flourish. Thiscan attract jobs and tax revenue in carbon-relevant sectors(such as renewable energy and production of more efficientappliances). However, it can also create an environmentalrace for the bottom, as regulations protecting the health andwell-being of urban inhabitants are cut in order to promote abusiness-friendly environment, thus negatively affectingadaptive action.

Creating policies to address climate change is not onlyabout goodwill or institutional capacity, it is also aboutunderstanding the inertia and endurance characterizingmany of the issues that adaptation and mitigation actions aresupposed to address. Power plants, refineries and otherenergy investments have long lifetimes. Similarly, this is alsothe case with water systems, roads, houses and other compo-nents of the built environment at risk from the impacts ofclimate change. Although increased research, developmentand actions to reduce emissions are required within the nextfew years to achieve the target of no more than a 2°Cincrease in the Earth’s average temperature, it will takedecades to centuries to move the world’s current energysystem away from its dependency on fossil fuels, the mainsource of GHG emissions. Urban form changes at slow rates,cannot be easily shaped by design and takes a very long timeto build urban infrastructures.

A key problem outlined in Chapter 2 is that actors andagents of climate change at all levels, including governments,NGOs and civil society, are, most often, preoccupied withimmediate and often localized interests and priorities; butthese same actors need to move within short timeframes toguarantee long-term and wide-ranging global interests thatcan seem remote and unpredictable at best. Much action onmitigation and adaptation will need to come from local actorsand agents, focusing their work at the local level where allthe impacts of climate change will ultimately be felt.Networks of local actors can further energize this movementand may accelerate action at the global level. This work mustinclude education and outreach to build broad-based supportfor mitigation and adaptation initiatives to increase theadaptive capacity of areas and populations that are mostvulnerable to the effects of climate change. It will also

require a shift in paradigm, from the current focus on inter-national responses to one that is more broad based andinclusive of actions at national and local levels.

Sources and drivers of cities’ GHG emissions

To explore the sources and drivers of urban areas’ contribu-tion to climate change is of utmost importance for severalreasons. First, transportation, energy generation, industrialproduction and other urban sources are associated withcities and their functioning. Each of these sectors consti-tutes a universe by itself, not only in terms of the types ofGHGs that they generate, or the factors explaining differ-ences in the levels and carbon intensities of their emissions,but also in terms of the mitigation opportunities that theyoffer, all of which will be briefly discussed here.

Energy is by far the most relevant sector for assessingGHG emissions, as the combustion of fossil fuels for electri-city generation, heating, cooling, cooking, transportation andindustrial production is the major source of GHGs. Theenergy systems that urban areas rely heavily on are shapedby the quantity of energy used, the energy structure (i.e. thetypes of energy forms used) and the quality of the energy(e.g. natural gas is less carbon intensive than coal). Variationsin emissions by one of the main urban energy sectors,electricity consumption – both between and within urbanareas around the world – depend on several factors thatpolicy-makers can address: access to the grid; the type of fuelused to generate electricity; technologies applied; andexistence of alternative sources of generation (renewable,nuclear, etc.).

Transportation is another key emitter that increases aseconomies grow, especially in developing countries, and asincomes rise. Emissions by the sector are expected tocontinue increasing in the coming decades. Particularly indeveloped countries, urban areas often generate smalleramounts of per capita GHG emissions from ground trans-portation than rural areas. Density plays a key role in thisdifference, and is one of the most important factors influen-cing differences both in the amount of energy used and GHGsemitted across urban areas. This should not lead decision-makers, however, to simply base their actions on a snapshot ofurban form at a particular moment in time. It should, rather,lead them to address the dynamics of such processes as theextent of automobile use, quality of public transit, land-useplanning and governmental policies, all of which determinethe impact of urban density upon energy use and emissions bythe transport sector. Policies aimed at reducing emissions bythe sector need to consider that differences in emissions for amode of transport (e.g. private vehicles) also depend onseveral factors: size and types of vehicles, efficiency ofengines, maintenance practices, vehicle-trip frequencies andoperating speeds, and driving behaviour.

Commercial and residential buildings are key sourcesof direct emissions, indirect emissions and emissions associ-ated with embodied energy (i.e. commercial energy used tomake products). These are related to onsite combustion offuels, public electricity use for street lighting and districtheat consumption, and through the materials used for their

construction. Decision-makers need to pay attention to suchfactors that determine emissions from buildings as the needfor heating and cooling (determined by climate conditions,but also by cultural preferences and access to monetaryresources), the construction of the building, the behaviourof building occupants, the type of fuel used, the size of thespace to be heated or cooled, and the orientation of thebuildings.

Two other key emitting sectors are industry and waste.Because many industrial activities are energy intensive intheir operation, their increasing dominance in theeconomies of such cities as Saldanha Bay in South Africa orShanghai in China (see Chapter 3) can make up a big part oftheir emissions. Mitigation policies and strategies need toaddress the following factors accounting for differences inindustrial emissions: location, size and age of the industrialfacilities, as well as the carbon intensity of their energysources. Although waste is a small contributor to globalemissions, rates of waste generation have increased duringrecent years, particularly in rapidly industrializing developingcountries that have been experiencing increasing affluence.Waste generation is linked to population, affluence andurbanization; yet – as exemplified by Barcelona (Spain),London (UK) and New York (US) – emissions from wastegeneration can be greatly reduced by such measures asefficient collection, and technologies for methane captureand storage, as well as for methane to energy conversion.

The second reason for highlighting the need for anunderstanding of the sources and drivers of GHG emissionsrelates to a twofold purpose of measuring emissions fromcities: inventories of emissions provide a basis for compar-isons and for inter-urban competition and cooperation; andthey constitute a crucial first step in identifying potentialsolutions. However, cities also rely on inward flows of food,water and consumer goods that result in GHG emissionsfrom areas outside the city.

Notwithstanding the importance of emission invento-ries, it has been difficult to develop a standardized globallycomparable methodology for GHG emissions at the local ormunicipal level. There are a number of reasons for this:

• It is difficult to attribute to cities emissions by suchsectors as aviation and shipping. For example, many ofthe passengers using major international airportssituated in or close to major cities may be fromelsewhere in the country, or may only be using theseairports for transit purposes.

• The different methodologies used to measure emissionscan result in different numbers (i.e. scope issues). Forexample, Scope 1 inventories only include directemission sources within the political boundary of a city,while Scope 3 would include all indirect and embodiedemissions (such as GHG emissions embedded in food).

• A wide range of boundary definitions are used to defineurban areas and cities. It is clear from Chapter 3 thatthe smaller the scale, the greater the challenges posedby ‘boundary problems’, which make it increasinglyhard to identify which emissions ought or ought not tobe allocated to a particular place.

Energy is by far themost relevant sectorfor assessing GHGemissions

It has been difficultto develop astandardizedglobally comparablemethodology forGHG emissions atthe local or municipal level


The above should lead policy-makers to be extremelycautious about statements or numbers on the total contribu-tion of urban areas to GHG emissions – not only because ofthe lack of an accepted definition of an ‘urban area’ or ‘city’,or of globally accepted standards for recording emissions,5

but also because little clarity exists on the relative allocationof responsibility from ‘production-based’ or ‘consumption-based’ approaches. This is illustrated by the fact that vastlydifferent proportions of emissions can be attributed to themanufacturing sector of Chinese or African cities discussedin Chapter 3, which produce goods for consumption in manyother locations around the world.

What is clear is that a large measure of the responsi-bility for the emissions in the producing country should beborne by individuals consuming the produced goods. Incontrast with most assessments of the urban contribution toclimate change, focused on the emissions that are producedby activities taking place within given territorial boundaries,Chapter 3, therefore, suggests an alternative approach whichalso considers the emissions associated with the consump-tion patterns of individuals. This idea acknowledges the factthat many agricultural and manufacturing activities thatmeet the needs of urban residents take place outside cityboundaries, and often in other countries. Furthermore, andmost importantly, it leads to the conclusion that unsustain-able levels of consumption – as partially determined by themarketing strategies of corporations, but which also drivethe processes of production – are crucial to understandingthe contribution that urban areas are making to climatechange.

Besides patterns of consumption, a variety of overrid-ing factors account for the different contributions of urbanareas to GHGs, both within and across countries. The firstare the various dimensions of geography that can be broadlycategorized as climatic situation, altitude and location inrelation to sources of energy resources (e.g. hydroelectricityand coal).

The second is the demographic composition anddynamics of a society given by changing age structures, andthe increasing trend (at least within wealthier groups)towards smaller households. Demographic dynamics relateto GHG emissions in very complex and shifting ways.

Urban form and urban density are the third factor,related to a series of social and environmental outcomes. Forinstance, the extremely low densities of many suburbanareas (particularly in North America and Australia) are associ-ated with high levels of household energy consumption andemissions as a result of sprawling buildings and extensive carusage. On the other hand, the extremely high densities ofmany developing country cities can be related to increasedhealth risks, and high levels of vulnerability to climatechange and extreme events. Some of the many factors deter-mining climate risks can be exacerbated by density: coastallocation, exposure to the urban heat-island effect, high levelsof outdoor and indoor air pollution, and poor sanitation.6

These same factors, however, can create opportunities forsimultaneously improving health and cutting GHG emissionsthrough policies related to transport systems, urbanplanning, building regulations and household energy supply.

Finally, the types of economic activities taking placewithin an urban centre are another key determinant of GHGemissions, not only because the dominance of industrialactivities has a huge influence on patterns of emissions, butalso because – as illustrated by many cities in South Africa –extractive activities and energy-intensive manufacturing,particularly if depending on fossil fuels, are obviously associ-ated with higher levels of emissions.

The multiple urban faces of climate impactsand vulnerabilities

Chapter 4 highlights the potential cumulative and multiplica-tive effects of loss of lives, damage to infrastructure and ofother climate-related impacts. It also addresses the distribu-tional nature of climate change impacts both within andamong cities. However, not all of the outcomes of climatechange are negative. As illustrated by cities as diverse asDurban (South Africa), Manizales (Colombia), New York(US) and London (UK), the potential also exists for cities toserve as sources of resilience to climate change, takingadvantage of opportunities to address multiple developmen-tal problems at once and to lead the world on adaptationefforts.

Chapter 4 also points to current findings on therecent and future trajectory and geographical variations inclimate hazards. For instance:

• Although showing significant regional variation, averagesea levels have been rising and are expected to continueto rise around the world, thus putting coastal urbanareas at risk from property damage, displacement ofresidents, disruption of transportation and wetlandsloss.

• Tropical cyclones and extra-tropical storms have beenincreasing in intensity since the 1970s.

• Severe precipitation events have become more intenseand more frequent, and are predicted to cause a greaterincidence of urban flooding.

• As a result of climate change, extreme heat events arepredicted to become more intense, longer lasting andmore frequent over most land areas.

Urban areas are already facing an array of hazards, with somethat are related to climate change and others that are not;but together these hazards may present a complex set ofcircumstances that will increase impacts. Heat wavescoalesce with urban heat islands and air pollution to puturban populations at increased risk from respiratory mortal-ity. When hitting areas subjected to processes ofdeforestation and erosion, heavy precipitation events resultin flooding and landslides, whose primary victims are popula-tions living in slums.

Climate events can also result in different sets ofsocial and environmental impacts upon the economicsectors, infrastructures and population groups of a city. Forinstance, severe weather events, including heavy precipita-tion and wind, can decimate the built environment,including homes and places of business. They can also

Unsustainable levelsof consumption …are crucial to understanding thecontribution thaturban areas aremaking to climatechange

Climate events can… result in differentsets of social andenvironmentalimpacts upon theeconomic sectors,infrastructures andpopulation groups ofa city


disrupt and cause lasting damage to highways, seaports,rivers, bridges and other components of the transportationsystems that urban centres depend on. These weatherimpacts can affect such infrastructures as water supply,sanitation and energy provision. They can also affect theinsurance industry and its beneficiaries by increasing thecosts of insurance coverage and can negatively affect notonly retail and commercial services, but also industrial facili-ties, especially if they are located in risk-prone areas ordepend on climate-sensitive inputs. Furthermore, they canmake it difficult for residents of informal settlements toconduct small-scale commerce, petty trading and artisantrades.

When considering how climate change will impactupon urban areas, it is important to distinguish between riskand vulnerability. The same risk factors (such as hurricanesand floods) can be experienced differently by differentindividuals, demographic groups, cities and countries. Mostclimate change risks have a high degree of regional and localvariation. The level of risk to an urban area from theseimpacts depends, in part, on how much of the city’s popula-tion and economic assets are located in high-risk areas (i.e.exposure). In many cases, exposure level will be a functionof the location of the city itself. Exposure can also be linkedto land-use planning within a city, including continued devel-opment in known hazardous zones, and the destruction ofnatural protective areas.

Similar climate change impacts are not experiencedthe same way by cities in developing and developedcountries. The degree to which urban areas are vulnerable toclimate hazards or can suffer negative impacts depends notonly on the nature and dynamics of physical hazards, but alsoon social and environmental factors such as the:

• integrity of infrastructure and urban planning, or lackthereof;

• availability of financial and human resources;• presence of disease and malnourishment;• availability of information and level of awareness of risk;

and• extent of dependence on natural resources.

Differences in climate impacts also exist between men andwomen, the elderly and children, and the wealthy and thepoor, both in developed and developing countries. Forexample, men and women differ in their livelihoods, familyroles, behaviours, access to assets and perceptions of risk.Both can be treated differently with respect to planning andrelief efforts during and after disasters. Impacts are alsofrequently more severe for the disabled, and ethnic andother minorities, who are frequently and relatively moredisadvantaged in terms of access to assets and adaptationoptions. The vulnerability of children relates more to theirphysiological immaturity or to their limited cognitive abilityand behavioural experiences, compared to adults. Thevulnerability of the elderly can depend upon such factors aspoverty (greater in developing countries), social isolation(more common in developed countries) or deterioratingphysical health and mobility.

It is also important to note the issue of compoundingvulnerabilities – that is, the fact that some population groupsfall into more than one such category (e.g. poor old women)and can thus find themselves dramatically constrained intheir ability not only to cope with future climate hazards, buteven to prepare for and respond to the varied stresses thatthey already face.

Government intervention can fundamentally improveurban resilience to climate change impacts through targetedadaptive finance, broad institutional strengthening and moreattention to the causes of vulnerability. The opposite,however, can also be the case. Maladaptive policies – such asineffective or completely lacking land-use controls, weakbuilding code standards or ineffective enforcement – havedirectly resulted in increased vulnerability of urban areas orof households and communities within them to sea-levelrise, flooding and coastal storms.

In order to improve resilience to climate impacts, ithas been suggested that urban governance should target themost vulnerable populations – namely, the urban poor andindividuals living in informal settlements. These two groupshave often been ignored in more conventional urbanplanning and intervention. Policies will need not only toreduce the vulnerabilities of existing populations, but also toaddress the underlying issues that permit settlement inmarginal and vulnerable urban areas in the first place.

Mitigation responses

Because cities represent concentrations of populations andeconomic activities with expanding energy demands forheating, cooling, lighting, transportation, industrial proc-esses, water provision, waste disposal and telecommun-ications, they can be seen as one ‘part of the problem’ ofclimate change. Reducing GHG emissions is, therefore, oneof the key policy challenges that cities face. Beyond this viewof cities as a major culprit in global climate change, however,there is also great promise for these same cities to become‘part of the solution’. Cities may play a major role in mitiga-tion efforts for three reasons. First, they have direct orindirect jurisdictional responsibility for some of the keyprocesses that may be involved in the production or reduc-tion of GHGs – processes such as transportation, energygeneration and use, land-use planning, and waste collectionand disposal. Second, by virtue of the fact that cities concen-trate populations and businesses, they may also makefeasible such potential solutions as mass transit and energysavings in office buildings. Third, they may act as a catalyst toother potential levels of action on climate change as munici-pal governments interact with stakeholders in the privatesector and civil society. Over the past two decades, in fact,cities have become a ‘crucial arena’ where the challenges ofclimate change are being addressed.

Chapter 5 notes that there are five key sectors wheremitigation actions are taking place in urban areas. Thesesectors are urban form and structure; the built environment;urban infrastructures; transport; and carbon sequestration.In terms of the first of these, urban sprawl is an area ofconcern for both developed and developing countries. This is

Similar climatechange impacts arenot experienced thesame way by citiesin developing anddeveloped countries

Over the past twodecades … citieshave become a‘crucial arena’where thechallenges ofclimate change arebeing addressed


so because distances travelled between home and work,education or leisure activities equate to a greater reliance onmotorized transportation. Sometimes sprawl has also led tomiddle-class urban fringe districts where more available landand a release from some of the building constraints of thecentral city has meant larger house sizes and higher percapita GHG emissions. In other cities, however, sprawl isfuelled by the growth of informal settlements.

In order to address these issues, many strategies havebeen used to limit urban expansion, reduce travel andincrease energy efficiency of the urban form. Some of thesetake the form of small- and large-scale regeneration projects(urban renewal), and these have taken place primarily indeveloped countries. Within developing countries there arefew mitigation initiatives that make explicit use of urbanform; when attempted, they are often constrained by a lackof capacity among local governments to implement themeffectively. They also have been criticized for their exclusivenature and potential for exacerbating social inequalities (e.g.the eco-city Dongtan in China).

The design and use of the built environment is an areathat is critical to urban mitigation efforts, and actions fallinto three broad categories. These are economic incentives,regulatory requirements and information programmes. Morerecently, a growth in voluntary public–private partnershipsand a mixing of these approaches has led to an explosion inthe range of approaches used, including micro-generationand new building materials. Nonetheless, built environmentprojects primarily take place within the cities of developedcountries, and have sometimes taken the form of efforts tohelp the urban poor. Some of these projects7 have been ledby grassroots organizations and housing co-operatives,suggesting that innovative forms of social organization areemerging and creating initiatives that address climate changemitigation, while also potentially taking on issues of socialand environmental justice. The combination of social andenvironmental gains may be particularly useful in developingcountries and for addressing such issues as fuel poverty.

Many of the urban infrastructure initiatives focusingon energy efficiency are primarily driven by such factors as adesire for energy security and financial savings, and – to alesser extent – by the opportunities offered by internationalinstruments such as the CDM. Both drivers may have helpedto keep these projects economically and politically feasible,but, at the same time, may limit their effectiveness in long-term GHG savings, as financial savings have sometimes ledto increased usage. Because of this, measures must be takenagainst the rebound effect, where increased efficiency leadsto higher energy consumption. Thus, energy efficiencyprojects need to be coupled with the development of low-carbon renewable fuel sources and efforts to reduce energyconsumption.

As noted above, the transport sector is a large contrib-utor to GHG emissions. Growth in GHG emissions alsoreflects a modal shift, since higher incomes increase theaffordability and desirability of private automobiles, andmiddle- and high-income groups within developing countriesmove towards the use of private vehicles and away frompublic transportation. Climate change mitigation schemes in

the transport sector may be grouped into seven categories,including low-carbon transport infrastructure; low-carboninfrastructure renewal; fleet replacement; fuel switching;enhancing energy efficiency; demand-reduction measures(for private motorized vehicles); and demand-enhancementmeasures (for public and other low-carbon modes of trans-portation, such as human powered).

Carbon sequestration involves removing carbon fromthe atmosphere, either through promoting natural carbonsinks (such as planting trees or protecting forests) or bytechnological means for carbon capture and storage. Whilecarbon sequestration schemes have mostly been on theperiphery of urban mitigation efforts, new technologies forcarbon capture and storage and international carbon financeare bringing carbon sequestration to the fore. Most carbonsequestration schemes at the urban level relate to tree-plant-ing schemes, as well as restoration or preservation of carbonsinks. Carbon sequestration projects combine well with citybeautification programmes where measures such as creatingand protecting green spaces and facilitating public access canbe brought together.

Despite the array of mitigation responses by urbancentres to date, a piecemeal rather than a strategic approachis very common. Furthermore, notwithstanding theexistence of initiatives to measure mitigation outcomes,8

there is limited information about the individual and collec-tive impact of existing responses, especially when theyextend beyond municipal buildings and infrastructuresystems or involve behavioural change. The reasons for thisinclude the relatively short time-scales involved and thefragmented nature of the data available, especially withregard to levels and reductions of GHG emissions within andacross urban communities and sectors.

Of the four types of municipal governance describedin Chapter 5, self-governing, the one mostly emphasized bymunicipal authorities, faces a limitation: frequently, munici-pal GHG emissions make up a small percentage of the totalcity emissions. This means that too much attention to theself-governing mode may detract resources from the broadermitigation challenges faced by a city. Seeking to governclimate change through the provision of infrastructure andservices holds the most potential in cities where municipalgovernments retain ownership or control of infrastructurenetworks, and where basic needs have been met. Because oftheir targeted and enforceable nature, taxation, land-useplanning and other regulation mechanisms can also be veryeffective in terms of reducing GHG emissions. Yet, these arealso the least popular approaches adopted by municipalgovernments and, therefore, the most difficult to sustainpolitically. The enabling mode of governing has significantmitigation advantages: it results in (relatively) low upfronteconomic and political costs, and can also increase the trans-parency and legitimacy of urban governance. However,enabling initiatives are restricted to those who are willing toparticipate, and cannot be enforced.

Chapter 5 also explores three modes of public–privategovernance of climate change action: voluntary, privateprovision and mobilization. The chapter uses the limitedavailable data on this relatively new phenomenon to draw

The design and useof the built environment is anarea that is criticalto urban mitigationefforts

Despite the array ofmitigation responsesby urban centres todate, a piecemealrather than a strategic approach isvery common


some preliminary conclusions. These approaches tend to beadopted by partnerships or networks, and to focus on theadoption of voluntary standards. They have the potential tooffer win–win options (i.e. tackling mitigation through aprogressive, inclusive and environmentally fair approach).They are also faced with problems, however: they are smallin scale and often politically marginal. They may serve toshift accountability away from actors with much higherresponsibilities for the bulk of (urban) GHG emissions.Although partnerships may provide shared resources, knowl-edge and other benefits, they are often fragile andthreatened by the potential of promoting the points of viewof a select group of individuals and serving powerful inter-ests at the expense of the disenfranchised.

Adaptation responses

Because mitigation efforts at all levels have so far not beenable to move the global climate system away from its currentand dangerous trajectory of change, adaptation actions areurgently needed to address both current and future climaterisks in urban areas. What decision-makers at different levelsdo today to cope and adapt will have an influence on thelives and livelihoods of millions of urban dwellers. Buildings,infrastructures, energy systems and other key components ofcities are long lasting. Therefore, what is designed and builtnow will be fundamental in coping with climate changemany decades into the future.

Urban populations have long had to cope with a widerange of risks to their economic activities, lives and liveli-hoods. In the absence of effective local government actions,these become the most frequent types of response toclimate change. Yet, these responses are generally smallscale; they do not address the underlying root causes ofvulnerability and are therefore best described as copingstrategies.

Wealth and access to assets, information or socialnetworks can help individuals to reduce the risk of negativeoutcomes. Wealth, for instance, allows individuals to buy,build or rent homes that can withstand extreme weather indistricts that have not been at risk from flooding. As illus-trated by such cases as Dhaka (Bangladesh) and Lagos(Nigeria), populations lacking access to these use otherstrategies to reduce the risks of negative outcomes. Most ofthe measures taken to help cope with climate events areimpact minimizing or impact reducing, rather than preven-tive.

Community-based adaptation is important in urbanareas, as it helps to address the limitations or inadequacies ofgovernmental intervention (such as in the provision of infra-structure and services); and because it can become animportant part in the enhancement of resilience to extreme,and increasingly unpredictable, weather events. Community-based adaptation is based on the premise that localcommunities have the skills, experience, local knowledgeand motivation, and that, through community organizationsor networks, they can undertake locally appropriate riskreduction. However, to be effective, community-basedadaptation depends on the actual existence of a collective

‘community-based’ organization in which the needs andpriorities of those most at risk or most vulnerable are repre-sented and actually taken care of in effective ways. It alsoneeds to focus on the reasons why the urban poor are dispro-portionately vulnerable to climate change, such as throughtheir greater exposure to hazards, the lack of hazard-reduc-ing infrastructure, the lack of state provision for assistanceafter extreme events, and the lack of legal and financialprotection.

Equally relevant can be other grassroots organiza-tions. For example, by enhancing the capacity of the urbanpoor to save regularly, by helping to identify and purchaseland for housing, and by promoting other actions of commu-nity organization, slum federations (such as in thePhilippines and India) are helping to build the resilience oflow-income households to many potential shocks.

Yet, community-based adaptation and grassrootsorganizations are faced with constraints arising from theimmense cost, energy and time required to construct,develop and maintain the key determinants of resilience forthe inhabitants of many cities in developing countries. Thesedeterminants of resilience include infrastructure andservices, warning systems, emergency responses, education,etc. In fact, most climate change-related risks exacerbaterisks already present, which are the result of inadequacies inlocal governments’ capacities or willingness to manage andgovern urban areas. Thus, there is a large deficit in the basicinfrastructure and services needed to address not only risksrelated to extreme weather and water constraints, but also‘everyday’ risks.

Cities in developed countries do not have very largeinfrastructure deficits. Most or all of their inhabitants live inbuildings that meet building standards, have access to educa-tion and are served by piped water supplies, sewers, drainsand solid waste collection. Therefore, their adaptationresponses are frequently relatively easier to design, imple-ment and fund. This does not mean that adaptation easilygets the political support that it deserves. Many cities needmajor upgrades in their infrastructure and should takeaccount of likely climate change impacts. Most cities need toexpand their capacity to anticipate and manage extremeweather events. Some cities are located on sites that are atrisk from the implications of climate change (such as coastalareas). Finally, key actors in many developed country citieswhich struggle with economic decline see climate changerisks as a distant danger.

Some components of effective adaptation responsescan be drawn from the analysis of different case studiespresented in Chapter 6. An essential first stage is the recog-nition among authorities and stakeholders that climatechange impacts need to be considered. Then an informationbase on current conditions (i.e. on impacts of past extremeweather and other disasters) needs to be developed.Involved parties need to build on community and districtassessments, as well as projections of future climate change,to develop risk/vulnerability assessments for the city.Strategic plans for the city as a whole and for its differentsectors should be developed in association with other stake-holders. Furthermore, measures should be undertaken to

Adaptation actionsare urgently neededto address bothcurrent and futureclimate risks inurban areas

Community-basedadaptation is important in urbanareas, as it helps toaddress the limitations or inadequacies ofgovernmental intervention


support those adaptation responses that are already takingplace.

Financing for adaptation revolves around two mainissues: whether funds will be available to cover the cost ofadaptation for urban areas, and whether there is the capacityto use such funds to ensure that the needed adaptation cantake place. Financing for adaptation can complement devel-opment assistance. While the latter can help focus on thedrivers of vulnerability that are associated with weak institu-tional capacity, the Adaptation Fund (see Box 2.2) cansupport the broader climate risk management strategies ofdeveloping countries. Furthermore, both can help toovercome the contentious issue of the boundary betweenclimate change adaptation and development, if designedwith this in mind.

A further related issue refers to the costs of adapta-tion. Most estimates of the costs of adaptation relevant tourban areas are estimates of the costs of adapting infrastruc-ture, and these are faced with some problems. First is theambiguity as to what to include under infrastructure(housing, for example, is sometimes included by the IPCC,sometimes excluded). Second is the assumption made thatcosts can be calculated by applying a small increment toexisting investment flows into infrastructure that is climatesensitive, with no account taken of the very large infrastruc-ture deficits. This leads to overestimates of the proportion ofinvestment allocated to developed countries and to under-estimates of the sums needed for Africa and other placeswhere there are very low/inadequate investment flows intoinfrastructure. The third is the belief that the availability of funding from international agencies is the ‘solution’ for adaptation, forgetting that local governments in many developing countries are often weak, ineffective and unac-countable to local populations. As a result, their capacity todesign and implement appropriate adaptation strategiesresponding to the requirements of those most at risk fromclimate change must be in doubt. Last, but not least, is theidea that ‘adaptation’ and ‘development’ can be keptseparate. As noted in earlier chapters, climate changeimpacts upon the ground are exacerbating non-climatechange impacts, and addressing both is inhibited by institu-tional/governance failures. It is therefore necessary to studycarefully what adaptation would involve in particularlocations and what component of this is related to the exist-ing infrastructure deficit.

It is also important to keep in mind that it will not bepossible to adapt to climate change impacts in a number oflocations – because adaptation is considered too expensiveor technically unfeasible. Such consequences are oftenreferred to as ‘residual damage’, and the number of suchlocations (and populations at risk) is likely to rise withoutsuccessful mitigation. In addition, the issue of migrants whoare forced to leave their homes due to future climate changeneeds to be addressed. As noted in Chapter 6, people whoselives and homes cannot be adapted in situ fall outside thescope of most national and international legislation. Thus,there have been some, though still marginal, calls for thedevelopment of new international legislation to address theconcerns of ‘climate migrants’ – perhaps in the form of an

international convention for persons displaced by climatechange.

ADDRESSING URBAN GHGEMISSIONS ANDVULNERABILITIES:CHALLENGES,CONSTRAINTS ANDOPPORTUNITIESBased on the findings of the previous chapters of this GlobalReport, this section explores the challenges, constraints andopportunities of efforts to decrease urban GHG emissionsand thereby enhance society’s resilience to climate change.The global mitigation challenge will be to achieve develop-ment paths that will bring down emissions by 2015 andstabilize them by the end of the century at 445 to 490 partsper million CO2 equivalent (CO2eq) by volume.9 Only in thisway can the global average temperature increase be keptbelow 2°C, which, as recognized in the Copenhagen Accord,is necessary to prevent harmful human interference with theclimate system.

Considering an estimated global population of 9billion by 2050 and an increasing urban share of that popula-tion, this means individual carbon footprints around theworld will have to be kept at an average of less than 2.2tonnes per year. Yet, annual per capita emissions in some UScities reach (or even exceed) 20 tonnes of CO2eq.10 Thus,there is a need to reduce the emissions of many cities andcitizens in developed countries (and even in some develop-ing countries) considerably. In order to address thischallenge, multilevel and multi-sectoral actions – includingmany measures at the urban level – will need to achieve:

• reductions in the quantities of fossil fuels used;• reductions in the carbon content of the fossil fuels used

(such as a switch from coal to natural gas); and• changes in the energy structure (such as increased

reliance on renewable energy sources) by switching toother sources of energy, while ensuring that the qualityof energy provision is kept.

For example, measures need to be undertaken to ensure thatelectricity, a key component of urban life, is generatedthrough less carbon-intensive energy sources.11

All of these require that the decline in the carbonintensity of fuels and the increase in both energy efficiencyand provision of low carbon-intensity clean fuels areachieved in such a way that the global amount of emissionsfrom fossil fuels is substantially reduced. And as can beconcluded from this Global Report, this is not always thecase.

Mitigation responses formulated so far have primarilyfocused on improving energy efficiency or reducing carbonintensity, which does not necessarily translate into a reduc-tion in the total amount of emissions. A focus on energy

Financing foradaptation cancomplement development assistance

There is a need toreduce theemissions of manycities and citizens indeveloped countries… considerably


Mitigation … isalready happening atdifferent levels ofgovernment, but notat all levels or withthe required effectiveness

Determinants ofmitigation responsesare the availabilityof financialresources, of technical expertise,as well as … thematerial infrastructure andcultural practices ofa city

efficiency savings in current infrastructure and devices (suchas cars) can result in a ‘rebound effect’ – that is, an increasein consumption (resulting, for instance, from the use ofsmaller engines but driving longer distances) following finan-cial savings in their operation. Furthermore, such a focus candownplay other more effective options. For example, sizeablerenewable energy installations, including wind, solar andhydropower, have received relatively lower emphasis.12 Thus,regulations and incentives by decision-makers operating atinternational and national levels need to be set, focusing on aportfolio of energy alternatives (i.e. not only on fossil fuels orbiofuels, but on combinations of all fuels that take advantageof and respond to differing circumstances and contexts).

Cities are and can contribute to addressing the mitiga-tion challenges of climate change in several ways:

• as initial seedbeds and niches for entrepreneurial experiments with radically new technologies (bycommercial private-sector actors);

• as lively laboratories for experimentation among emerging and future-looking communities (such asHammarby Sjöstad in Stockholm, Sweden13) that shareparticular perceptions, visions and ideas as to how tomove urban communities away from current unsustain-able development paths; or

• as communities that build networks and platforms (suchas workshops and conferences) to facilitate theexchange of knowledge and experiences, as well as thearticulation of best practices.14

Depending on their national contexts and histories, urbanlocal authorities have a highly variable level of influenceover GHG emissions. They can induce emissions reductionsin the energy sector through measures such as retrofittingcommercial, domestic and municipal buildings, by switchingtraffic lights to energy-saving bulbs, etc. Besides havinginfluence over the efficiency of their transportation fleets,they can implement transport planning policies whichencourage alternatives to the private car, such as theTransmilenio in Bogotá (Colombia). They can design zoningmeasures to promote certain patterns of settlement, energyefficiency measures in new buildings, and standards fordomestic and commercial buildings, as exemplified by theexperiences of London (UK) and Chicago (US). They canimplement programmes to reduce GHG emissions in thewaste sector, such as through methane capture. Non-governmental actors such as private-sector organizations arenow voluntarily involved in actions to decrease energy usein commercial buildings. A similar movement is happeningwithin civil society groups, such as the ‘transition towns’movement.15

The number of actions currently taking shape showthat involved stakeholders do acknowledge the urgency ofmitigation, and demonstrate their awareness that actionshould be taken now to avoid abrupt or irreversible impacts.Mitigation, indeed, is already happening at different levels ofgovernment, but not at all levels or with the required effec-tiveness. As indicated in Chapter 2, there are manychallenges faced even by such ambitious endeavours as the

European Emissions Trading Scheme and the mitigationresponses of the UK and Germany.16 Furthermore, althoughclimate change is firmly on the urban policy agendas in bothdeveloped and developing countries, it remains a marginalissue in terms of implementation.

Diverse institutional factors explain the challenges,constraints and opportunities of mitigation responses bylocal authorities. The first relates to the influence of thecontext-specific interactions between different tiers ofgovernment on local authorities’ response capacity (multi-level governance). International and national policies providethe enabling – but also constraining – context within whichurban responses are framed; determine the autonomy andcompetencies – the duties and powers – for municipalauthorities to act in response to climate change; and enablepolicy integration within and between local authorities.Another set of institutional factors shaping local authorities’mitigation responses is their institutional ability to imple-ment and enforce policies and measures. In many policyareas, municipal authorities, especially but not exclusively indeveloping countries, are unable or unwilling to enforcebuilding codes, land-use zoning, fossil fuel standards andother regulations.

Two other factors are critical for the development ofmitigation policies – namely, the dynamics of networkcreation and leadership – the latter both at the individualand institutional levels. Local Governments for Sustainability(ICLEI), organizations compiling and disseminating expertknowledge such as the IPCC, the United Cities and LocalGovernments and the Urban Leaders Adaptation Initiative,among other international, national and municipal networksof governmental and non-governmental organizations, havealso been important in developing municipal capacity.17

Evidence suggests, however, that these have been moreimportant in developing the capacity of those municipalitiesthat are already leading responses to climate change.Individual political champions and organizations, usingclimate change as a means and window of opportunity forfostering organizational reputation, have been equally funda-mental in shaping action. Yet, if authorities lack the financialand technological resources to execute programmes, thepower of leadership and of these networks to affect changecan be limited.

Of no lesser relevance as determinants of mitigationresponses are the availability of financial resources, oftechnical expertise, as well as the weight of such structuraland enduring factors as the material infrastructure andcultural practices of a city. For instance, the mitigationchallenges in the transportation sector will be strongly deter-mined by the urban form of a city, with high-density areasoffering compatibility with options to develop metros, tramsand other high-efficiency modes of public transportation,while sprawling low-density areas are more compatible withsystems of buses and minibuses to cover commuting needs.Options to reduce emissions are constrained by the fact thatinvestments in power plants, industrial facilities and othercomponents of the urban environment have long lifetimes.As for financial resources, given the many competingdemands in urban areas, local authorities lacking the money


to provide even basic services for their constituents areunlikely to invest in the mitigation of climate change.Furthermore, the international financial resources availablefor mitigation (and adaptation) activities under the UNFCCCand the Kyoto Protocol (see Boxes 2.2 and 2.3) are quitesimply not sufficient to meet the requirements, particularlyof developing countries. As discussed in Chapter 6, this isparticularly the case in cities, as very limited resources haveso far been made available for initiatives in urban areas.

It is likely that GHG emissions will continue toincrease until 2030 even if effective actions are taken now tostabilize emissions around the end of the century, anddespite current commitments within the Kyoto Protocol.18

Thus, adverse impacts of projected climate change andvariability are inevitable, and urban centres will be particu-larly at risk. Regardless of the scale of mitigation undertakenover the next two to three decades, adaptation action will benecessary, which will be another challenging and fundamen-tal dimension of the urgent response to climate change.

The responsibilities of local authorities with regard tothe built environment, infrastructure and services that haverelevance for adaptation include:

• urban planning and regulatory instruments designed toinfluence land availability and to authorize and overseehazardous activities that can produce disasters;

• provision and pricing of various public services, infra-structure and resources; and

• enabling, proactively facilitating and coordinatingactions to manage hazards through partnerships withthe private sector, the academic sector, non-governmen-tal and grassroots actors (e.g. households andcommunities) to reduce risk.

Each urban centre may use these areas of responsibility todesign adaptation actions. However, the particularities –often determined by the national contexts of these urbancentres – will dictate which of these measures will be mosteffective.

As with mitigation, adaptation is already taking place,at least on a small scale, and the world is witnessing thebeginnings of city-based adaptation strategies in some urbancentres. As yet, however, too few cities have developedcoherent adaptation strategies. Furthermore, in contrast tosuch sectors as agriculture or forestry, there is relativelymuch less explicit city-wide attention to urban adaptation. Infact, most of the literature on climate change adaptation incities is on what should be done, not on what is being done,the main reason being that too little is actually being done.The relatively lower emphasis on adaptation, and particularlyon urban adaptation, is partly a result of the existing struc-ture of incentives under the Climate Convention. Forinstance, funding is available19 for mitigation activities suchas landfill gas capture and for electricity generation, fortransportation or carbon capture from reforestation andconservation of forests. However, while very little (only 8.4per cent of the CDM projects are urban) is readily availablefor urban mitigation projects, practically nothing is allocatedto adaptation efforts at the city level.20

Among urban areas, this relatively low interest inadaptation can also be related to the fact – clearly illustratedby Durban (South Africa) – that getting more widespreadattention by city and municipal governments to climatechange adaptation requires clear and detailed risk assess-ments (knowledge). It also requires a better understandingof how adaptation measures can serve and be integrated notonly within disaster risk reduction, but also within suchcomponents of the development agenda as land-useplanning, as well as access to water, sanitation and housing.It also depends on diverse institutional factors, in addition toleadership and local authorities’ willingness to act. Forexample, effective adaptation actions can depend onwhether authorities have the autonomy, resources anddecision-making power to design and implement actions onthe built environment, infrastructure and services that haverelevance for adaptation; and whether and how adaptationoptions and challenges are related to such developmentissues as the need to protect the poor or to provide land andshelter for them (such as Manizales, Colombia, and theHomeless People’s Federation of the Philippines).21

A fundamental challenge in this context relates notonly to whether adaptation is responding effectively topotential climate change impacts in different sectors, butalso to social equity issues – that is, whose needs are served(and whose are not) by adaptation responses, especially inrelation to income, gender and age. For instance, are theadaptations aimed at protecting the wealthier groups anddistricts; or those living in informal settlements; or womenand their particular risks and vulnerabilities; or the city’smost economically important assets; or the city’s populationsmost at risk? Decision-makers can be more effective andlegitimate if they include these groups – or at least theirgenuine representatives – in the process of addressing thesequestions.22

It is not only the city authorities of some earlyfrontrunners that are responding to the adaptationchallenges of climate change. Households and communitiesare already coping with climate-related hazards – forexample, by raising plinth levels, saving money and by partic-ipating in community initiatives to clear blocked drainagechannels to respond to the impacts of flooding (see Chapter6). However, these cannot be substitutes for serious govern-ment investment and action to improve drainage andsanitation, water supplies, roads and other hard infrastruc-ture that is so crucial for risk reduction, or for a city-wideprovision of urban services, as well as warning andemergency responses systems.

In the urban areas of many developing countries,household, community and government adaptationresponses will need to happen in the context of adaptation(or development) deficits. In many cities of developingcountries, at least a percentage of their populations lackwater, sanitation, health services, shelter, soundemergency policies and other factors to adapt to thecurrent range of climate variability, let alone to any futureclimate change impacts. It is impossible to adapt or climate-proof infrastructure, services and emergency responsesthat do not exist.23

Too few cities havedeveloped coherentadaptation strategies

In the urban areas ofmany developingcountries … adaptationresponses will needto happen in thecontext of adaptation (or development)deficits


Another key challenge concerns the social impacts ofadaptation measures. Actions such as control of urbangrowth in risk-prone areas and investment in storm andsurface drainage systems can increase the vulnerability ofsome populations. If not carefully designed, they have thepotential to displace informal settlements – especially thosealongside existing drains and rivers. Furthermore, they canconstrain a population’s capacity to make their livelihoods;they can shift risks from the populations of one district tothe inhabitants of another district; and they can shift risks tofuture generations.

ADAPTATION ANDMITIGATION:RELATIONSHIPS WITHURBAN DEVELOPMENT AND POLICYAlthough a distinction between climate change adaptationand mitigation is deeply set in climate change policy andresearch, some cities tend to look at the world differently.Early experience with both adaptation and mitigationplanning in developed country cities suggests that urbanleaders and stakeholders resist focusing on one and not theother, and that they find it difficult to consider eitherwithout considering sustainable development goals anddevelopment pathways more generally at the same time.24 Infact, the goal is sustainable development for their cities, andclimate change responses are either a means towards thatend or impediments to achieving that end. In this context,attention needs to be given not only to the implications ofmitigation and adaptation for urban development, but also tothe synergies and trade-offs between actions addressing bothmitigation and adaptation and other dimensions of policy-making. However, experiences from many cities indeveloping countries contradict this, as their leaders andstakeholders tend to consider developed countries theculprit of climate change and, thus, responsible for mitiga-tion. Such cities therefore tend to focus on adaptationinterventions.

Cities can respond to concerns about climate changeimpacts in two ways: by contributing to mitigation or byadapting to possible impacts – either of which can promoteurban development or impede it.

Climate change mitigation and urban development

In the coming decades, urban authorities will – in manycases and in many regions – find that the need for global,national, regional and local climate change responses posessignificant concerns. The urgency and severity of thischallenge cannot be overstated. Recent analyses of potentialsfor GHG emissions reduction and efficiency improvement,given current global trends and potentials for knowntechnologies, make even relatively moderate goals such as

stabilization at 445 to 490 parts per million of CO2eq (inorder to keep average global warming no higher than 2°C)virtually unachievable unless every major technologicaloption realizes the most optimistic hopes for it (includingaffordable carbon capture and sequestration from coal).25 Inother words, the world seems headed towards climatechanges that are even more severe than the soberingdescriptions in Chapter 4. Meanwhile, at the CopenhagenCOP in December 2009, low-lying island states and othervulnerable developing regions argued that any stabilizationlevel that means average warming above 2°C impliesunacceptable levels of impacts and must be avoided. Twoapparent crises lie ahead: a crisis of emerging impacts invulnerable cities as they become ever more urgent and acrisis of global responses to growing pressures for mitigationand adaptation, which are likely to be sources of greatcontroversy and, perhaps, forceful policy developments.

Globally, the mitigation challenge is to reduce GHGemissions from buildings, industry, transportation, energyproduction and land use, and to reduce or reverse deforesta-tion. As stated earlier, emissions reduction focuses onefficiency improvements in buildings, industry, transporta-tion and energy production, and shifting energy productionand use from GHG-emitting fossil sources to alternativessuch as renewable energy, nuclear energy and ‘decar-bonized’ energy from fossil sources.26

It is important to note that mitigation policies canrepresent opportunities for cities and their developmentprospects. As exemplified through the experience withICLEI’s International Local Government GHG EmissionsAnalysis Protocol, in many cases, actions by cities to reducetheir GHG emissions from systems under the jurisdiction ofmetropolitan governments actually save them money, suchas through increases in the efficiency of urban lightingsystems or in public transportation systems that reduce coststo the city’s budget.27 Less directly, cities can partner withtheir own private-sector operators of industrial and trans-portation systems to seek reductions in GHG emissions fromprivate-sector sources, with city policies (such as taxation)encouraging or discouraging such actions. Even less directly,new energy facilities that help to reduce GHG emissions –such as bioenergy and other renewable energy productionfacilities – will need to be located somewhere, and cities canseek to be their sites, creating jobs and tax revenues.

But global pressures to push the boundaries of climatechange mitigation are likely to be a challenge for urbandevelopment as well. Two potential impacts are especiallyimportant. First, if an urban area’s economy depends, evenin part, on fossil energy production, it is likely to beadversely affected by any move away from fossil energy.There are many examples of cities whose economies arebuilt, in part, on coal, oil or natural gas production, such asin Nigeria, Angola, China and India.

A second impact is that energy costs and prices arelikely to increase in most parts of the world as energysystems shift from relatively low-cost fossil energy sources tosomewhat more expensive alternative energy systems.Because affordable energy is vitally important as a driver ofthe development engines of many cities, this could become a

Attention needs tobe given … to thesynergies and trade-offs betweenactions addressingboth mitigation andadaptation

Global pressures topush the boundariesof climate changemitigation are likelyto be a challenge forurban development


challenge for sustainable development – especially in citieswhose development paths are likely to be especially energyintensive. In most cases in developing regions, paths forsocio-economic and technological development implyincreases in GHG emissions, not reductions in emissions,including both emissions from the cities themselves andemissions from systems that meet urban needs, such aselectric power plants located elsewhere.

However, local authorities often play broader roles, aswell, in shaping the development choices of their urbanareas, their larger regions and their countries, and theseroles have implications for climate change mitigation morebroadly than within their own boundaries alone. They arethe focus of driving forces for climate change responses,including financial resources, information and communica-tion systems and media, and both technological and policyinnovation. Where public decision-making is based ondemocratic processes, local authorities can dominate ‘one-person/one-vote’ political contests and thus influencenational voting patterns.

There are both synergies and trade-offs betweenactions addressing the mitigation challenge and other policydimensions (such as industrial development, energy, healthand air pollution).28 As illustrated by Mexico City, Denver(US) and many Chinese cities, climate change mitigation ismore an outcome of efforts driven by economic, security andlocal environmental concerns, or simply by the need to be atthe forefront of initiatives among a peer group of cityleaders, rather than being a strategic priority.29 It is there-fore necessary to take advantage of existing synergiesbetween climate protection and other development priori-ties. For instance, strong synergies exist in thetransportation sector between climate change and energysupply and security. Measures replacing oil with domesticbiofuels can reduce both emissions and reliance on oilimports (such as in Brazil). A more decentralized electricitysystem based on new renewable generation may reduce gasimports.

A key question is whether cities have the potential totap into options such as carbon markets opened by the KyotoProtocol.30 For example, could the construction or buildingmaterials industries receive financing from the CDM orsimilar mechanisms for producing cement (or other materi-als) which incorporates carbon capture and storage? Suchcarbon credit trading could, potentially, be a way to subsidizethe construction of adequate housing for low-income groupsin developing countries. This and other options could open acompletely new discussion dealing with synergies betweenGHG emission control and poverty reduction.

Policies addressing other environmental and socialproblems, such as air pollution or provision of shelter to thepoor, can often be adapted at low or no cost in order toreduce GHG emissions and improve the health of thepopulation simultaneously, especially in developingcountries. The burning of fossil fuels is linked to bothclimate change and air pollution. Thus, reductions in theamount of fuel combusted will result in both lower GHGemissions and lower health and environmental impacts fromreduced emissions of air pollutants. Aware of these co-

benefits, organizations such as the World HealthOrganization and the US Environmental Protection Agencyhave applied, at the urban and national levels, environmentalassessments of the co-benefits of addressing both air pollu-tion and other issues (such as economic costs and energy).This has helped to introduce policies that address local pollu-tion and GHG emissions together.31 However, attentionneeds to be given not only to the synergies, but also to theconflicts between these policy domains. For instance,increases in the energy efficiency of vehicles can result inincreased atmospheric emissions, and thus in negativehealth impacts, if vehicle travel distances increase or driversswitch to vehicles with larger engines (the ‘reboundeffect’).32

This means that trade-offs may exist between mitiga-tion and other policy domains. For instance, securityarguments may impel countries to increase their depend-ence on internal reserves of coal rather than relying onnatural gas imports.33 Use of biofuels that are dependent oncrops such as corn has been linked to food shortages andcost increases as farmers switch food-producing croplands tomore profitable biofuel crop cultivation. This may also be anunintended effect of government subsidies aimed at increas-ing production of biofuels, but making the growing of foodcrops less profitable.

Climate change adaptation and urban development

Adaptation-related issues for urban development across theworld include two dimensions: first, the implications ofclimate change impacts for urban development projects thatare likely to call for adaptations; and, second, the relation-ships between adaptation action to reduce the impacts ofclimate change, on the one hand, and urban development,on the other.

Climate change poses particularly severe threats forurban development in those areas that are most vulnerableto climate change impacts.34 For example, many cities arelocated in coastal areas and river valleys, as well as areaswhere the economic base is rooted in climate-sensitivesectors, such as agriculture, forestry or tourism, and areaswhere these regional climate-related activities face increasedcompetition with population and economic growth. Ifclimate change is relatively severe in local contexts ratherthan moderate, some cities will find that incremental adapta-tions that protect current activities and ways of life may nolonger be adequate.

A current example of what future climate changecould mean for urban development can be found in the polarregions of the world, where temperature increases (andemerging sea-level rise) are not only affecting urban infra-structure as the permafrost melts, but are irreversiblydestroying polar ecosystems and indigenous ways of life thatare closely linked to them.35 In these and similar cases,adaptations that are ‘transformational may be required’, suchas changes in land uses and movement of investment awayfrom vulnerable areas, or shifts in directions of urban devel-opment to different economic sectors or land uses. Climate

There are bothsynergies and trade-offs betweenactions addressingthe mitigationchallenge and otherpolicy dimensions

Some cities will findthat incrementaladaptations thatprotect currentactivities and waysof life may no longerbe adequate


Most … adaptationoptions offer considerable co-benefits… for urbandevelopment and/orenvironmental stressreduction in thenear term

Neither mitigationnor adaptation alonecan protect theworld from theundesirable impactsof climate change

change impacts are therefore a critically important challengefor urban development, and if climate change is severe(rather than moderate), the number of cities at risk will bemultiplied many times over.

Experience suggests that, given human resources andaccess to knowledge, urban dwellers often have impressivecapabilities to adapt in ways that are good for their develop-ment, even with limited financial resources. For example,low-income residents of Lagos (Nigeria), Dhaka (Bangladesh)and Dar es Salaam (Tanzania) already cope with a range ofclimate-related challenges, especially seasonal flooding.36

This is particularly evident where effective grassroots organi-zations are active. This is not to say that decisive action is notneeded at all levels; but it is important to note the manyactions are already being undertaken by households andcommunities – frequently in the absence of actions by localgovernment and other stakeholders.

One of the most fundamental challenges in relatingclimate change adaptation with urban development in manyregions, however, is a limited capacity to identify vulnerabili-ties and adaptation pathways, along with a limited capacity tomake adaptation happen. Many small- and medium-sizedcities, especially in sub-Saharan Africa, South Asia andCentral America, currently show low levels of capacity toadapt to the current range of climate variability, let alone anyfuture climate change impacts. Problems in many such citiesinclude a lack of provision for infrastructure (including all-weather roads, piped water supplies, sewers, drains,electricity, etc.), urban social services (such as health andeducation) and institutional capacity.

Yet, many cities have shown an ability to adapt to localclimate conditions, whether related to climate change ornot; and where climate change adaptation is being consid-ered seriously (in urban areas from Bangkok, Thailand, toMelbourne, Australia), in nearly every case adaptationoptions are being identified that are relatively low cost andhave broad constituency support.37 Some developingcountry cities have moved beyond option identification toadaptation planning (such as Durban and Cape Town, SouthAfrica).38 Furthermore, most of the adaptation options offerconsiderable co-benefits – that is, benefits for urban devel-opment and/or environmental stress reduction in the nearterm, as well as added resilience to impacts of climatechange in the longer term, which is often critically importantin sustaining attention to adaptation while impacts aregradually emerging.

There are positive examples of cities, such as inManizales (Colombia) and Ilo (Peru), that are taking steps topromote development and reduce vulnerability at the sametime. These cities have implemented actions to preventrapidly growing low-income populations from settling ondangerous sites. Although these actions have not beendriven by climate change concerns, they illustrate how pro-development and pro-poor policies can enhance adaptivecapacity. Conflicts and trade-offs between developmentpolicies and adaptation are also possible, as in the develop-ment of infrastructure whose design and construction havethe potential to displace informal settlements.39

Mitigation and adaptation: Seeking synergiesrather than conflicts

It is now known that neither mitigation nor adaptation alonecan protect the world from the undesirable impacts ofclimate change. Both must be a part of the global response.Mitigation is essential in order to keep climate changeimpacts as low as possible; but some impacts can no longerbe avoided. This is so because progress is slow on interna-tional agreements to implement mitigation, and strategiesfor GHG emission stabilization in major developing countriesare unclear at best. Adaptation is, therefore, essentialbecause some impacts will not be avoided. It is clear thatcosts will be a constraint for some locations and populations,and adaptation will be limited in its ability to reduce costsfrom abrupt events, at least in the short run. And, as notedabove, some of the impacts are beyond the scope of adapta-tion: the so-called ‘residual damage’. While allocatingresources for mitigation and adaptation, it is essential to findsolutions for the populations and industries that may bedisplaced by the impacts of climate change.

Meanwhile, early initiatives with either climatechange mitigation or adaptation planning suggest that someurban local authorities and stakeholders are unwilling todiscuss mitigation or adaptation options separately, withoutplacing these discussions in the context of where the cityand its citizens want to go in the longer run.40 Cities are oneof the most important of all the world’s settings for integrat-ing actions to reduce vulnerabilities and mitigationresponses as they relate to broader social and economicobjectives, such as job creation, improvements in the qualityof life, and access to health and water services. The fact thatclimate change response planning often catalyses thesediscussions within communities is one of its most importantco-benefits.

A major problem is that mitigation and adaptationoptions often differ in important ways. For instance, theytend to differ as to when benefits are realized (mitigationbenefits lag in time, while adaptation benefits may be nearerterm), where benefits are realized (mitigation is global whileadaptation benefits are more localized) and what sectors arethe focus of action (mitigation focused on GHG emitters orsinks, and adaptation focused on activities, infrastructureand population segments sensitive to impacts). Furthermore,it is also important to note that mitigation actions are urgent.If no action is taken within the next ten years or so, theimpacts will exponentially increase. This is less the case withadaptation action, which can be phased in time and whichwill be a continuous process for many decades to come.These differences substantially complicate attempts byurban areas (or by the countries and regions whose policiesaffect them) to develop integrated climate change responsestrategies.

Pathways to mitigation and adaptation can bemutually exclusive and competitive alternatives – such asdevelopment investments in alternative energies which donot enhance resilience in vulnerable areas versus policies tomove development activities away from vulnerable areas;41

but they may also be complementary and reinforce each


other. A simple example of this would be building insulation,which can reduce the need for burning fossil fuels whileenabling adaptation to increased temperatures projectedwith climate change. An important general guideline is thatmitigation and adaptation options which offer synergies andcomplementary pathways should be given special attention.For example, mitigation options that reduce net GHGemissions – such as tree-planting and other biomass sinkpreservation and/or restoration, along with regional or localrenewable energy development – can be complementaryparts of an overall mitigation strategy. However, this synergycan be taken one step further with the addition of adaptationbenefits. Tree-planting or forest preservation, for instance,can also be an important part of an urban adaptation strategyto prevent heat-island effects, thereby preventing an array ofcascading negative effects such as heat-related morbidities,mudslides and coral sedimentation, etc.

In many cases in urban areas, the focus is on invest-ment in major infrastructure that lasts for a number ofdecades: transportation systems; commercial, residential andgovernment buildings; and industrial development. Theseinvestments can profoundly shape both urban mitigation andadaptation not only in the short term, but for as long as half acentury or more.

Currently, and with some notable exceptions, mosturban initiatives that might be associated with mitigation oradaptation are fragmented, and historically much of thepolicy attention has been focused mainly on mitigation, withlittle or no consideration of adaptation. In many cases, thefocus is not on climate concerns but on energy security andother development priorities related to economic growth.42

Even where existing initiatives explicitly address mitigation,they often focus only on one aspect of the whole issue (suchas energy efficiency, or even, more narrowly, energyefficiency in metropolitan public-sector functions).43

Only a handful of city-wide initiatives – such as inLondon (UK), Durban (South Africa) and New York (US) –are beginning to grasp the need to address at least some ofthe complex linkages between mitigation, adaptation anddevelopment, and thus have launched mitigation and adapta-tion programmes. For instance, to increase the uptake ofdecentralized energy technologies in London, developmentsover a certain size are required to meet 20 per cent of theirprojected energy needs through onsite low-carbon or renew-able energy generation,44 thus promoting new economicactivities and the creation of green jobs. Furthermore,national and local authorities have already identified adapta-tion responses to three key climate risks – floods, droughtand overheating – thus opening alternatives to avoid damageto infrastructure, increased mortality among the aged andother impacts that might constrain the livelihoods of somepopulations. This means that climate change responses aregetting the necessary ingredients to move towards moreintegrative approaches.45 However, even these exemplarycases illustrate the challenges of responding to climatechange.

FUTURE POLICYDIRECTIONSThis section explores future policy directions for achievingclimate-resilient cities, reflecting on both recent policydevelopments and more general long-term policy needs. Inthe face of climate change, policy decisions and actions are not just the responsibility of a city, or of its country or region, or of the international community more broadly –or even of governments alone at any of these levels. Urban development will be shaped by the policies of alllevels of government, of private-sector organizations, of non-governmental issue-oriented institutions, of researchcommunities,46 and of representatives of local communitiesand civil society organizations. The challenge, and it is animmense one, is to knit together a global response to urbanneeds and potentials in which a wide variety of partners eachcontribute what they do best – for instance, combining theresources available at large scales with the innovativenessand knowledge of local realities available at local scales.

From this perspective, this section outlines someprinciples for policy development at all levels and discusseswhat policies should be considered at the international,national and local levels and, more briefly, by non-govern-mental partners, to strengthen planning and decision-makingin urban areas in response to global climate change.

Principles for policy development

Several principles are fundamental to an integrated multi-partner approach:

• No single mitigation or adaptation policy is equally wellsuited to all cities. Reflecting a common saying that ‘onesize does not fit all’, cities are so diverse in terms of theset of societal and environmental drivers of their GHGemissions, their governance structures, their vulnerabil-ities, adaptive capacities and development aims thatpolicy approaches should recognize and be sensitive tothe diversity of urban areas worldwide.

• The appropriate approach is not to try to preciselyproject future climate change and socio-economicconditions, which is burdened by far too many uncer-tainties to encourage decision-making, but to take anopportunity/risk management approach in a sustainabledevelopment perspective: considering not onlyemissions but also risks that are present in a range ofpossible climate and socio-economic futures.

• Policies should emphasize, encourage and reward‘synergies’ and ‘co-benefits’ (i.e. what policies can do toachieve multiple objectives related to both developmentand climate change response goals).

• Climate change policies should address both near-termand longer-term issues and needs. Near-term perspec-tives are likely to focus on relatively straightforward ‘noregrets’ decisions with, first, few or no net costs, offer-ing substantial co-benefits for urban development (suchas increasing resilience to climate variability; reducingchronic environmental stresses, such as poor drainage;

Mitigation andadaptation optionswhich offer synergies andcomplementarypathways should begiven special attention

No single mitigationor adaptation policyis equally wellsuited to all cities


or addressing critical current needs of especially vulner-able populations who will only get worse with climatechange); and, second, with broad stakeholder supportand representation, not only of the better off, but alsoof populations more at risk from climate change (thepoor, women, children, the elderly, the disabled, ethnicand other minorities, etc.). Longer-term perspectivesneed to consider risk management for more substantialmitigation pressures and adapting to more significantimpacts, focused on contingency planning for a range ofpossible climate/development futures, monitoringemerging climate and policy conditions, and reassessingrisks periodically.

• Policies need to recognize that institutional roles andpotentials differ between scales and sectors of action. Inrecent history, too often well-intentioned initiativesdeveloped at large scales and implemented top downhave discouraged local action by imposing dauntingbureaucratic requirements as a condition for access toavailable resources.47 Meanwhile, initiatives developedand implemented at small scales and implementedbottom up (such as community-based adaptation) oftenlack financial and other resources to undertake thenecessary investments in urban infrastructure andservices, may lack valuable information, and may lead toactions that have adverse consequences for other locali-ties. The challenge is to design new approaches thatsupport multi-scale, multi-sector action, rooted in newkinds of mutual sensitivities, in order to realize thediffering and often complementary potentials of a widerange of partners (Chapter 6).48

International policies

International public-sector policies related to urbanresponses to climate change should be supportive andenabling without being directive or constraining (see alsoBox 7.1):

• Resources. The international community has access tovitally important financial resources that can beprovided to support many vulnerable cities that needadditional resources to respond to climate change. Forexample, international policies should include muchmore significant financial support for climate changeadaptation in vulnerable cities, for investment in aportfolio of alternative energy options, and to supportmitigation partnerships between local governments andlocal private-sector actors. In particular, it is essentialthat action is taken to facilitate the use of theAdaptation Fund and the CDM for initiatives in urbanareas.

• Information and options. The IPCC is already helpingcities and influencing development pathways by provid-ing information about climate change science andresponse options, alerting local leaders (and the peopleto whom they listen) to emerging issues and resolvingsome disputes about scientific facts. Internationalpolicies should continue these roles, with increasedattention both to widening the spectrum of mitigationand adaptation alternatives available for urbanresponses, and to improving information about thecosts, benefits, potentials and limits of the options. Asimilar role has been played by the Clinton ClimateInitiative and ICLEI (see Box 2.7), which have beenprominent in the exchange of ideas, best practices andexperiences, at least for urban areas that are already atthe forefront of climate change responses.

• Reduced bureaucratic burdens. International policiesshould do a better job of balancing legitimate concernsabout accountability (such as establishing ‘additionality’through detailed quantitative analysis) with a need tomake access to support much easier, simpler and lessbound up in expensive analysis. Options might include awider use of third-party intermediary (‘boundary’)organizations to disperse resources and monitorperformance. Likewise, streamlined approaches forapproving investments in certain types of projects that,time and again, have been shown to yield climatechange-related benefits should be developed andapproved (e.g. through the CDM). Likewise, in order toease access to carbon finance for cities in developingcountries, the CDM Executive Board should approvethe new city-wide programme of activities methodologythat was recently submitted for their consideration.49

National policies

As illustrated by some countries – such as the UK, Germany,Norway, Brazil and the Republic of Korea – the mitigationresponses of national governments can go beyond theendorsement of international climate conventions andaccords. Driven by reasons as diverse as energy security andan actual concern for the implications of climate change,they may engage in the design and implementation ofnational mitigation strategies and adaptation planning.However, from the perspective of urban areas, nationalgovernments generally assist development by determining

International public-sectorpolicies related tourban responses toclimate changeshould be supportiveand enablingwithout being directive orconstraining


Box 7.1 Key principles for urban climate change policy development: The international community

There are three main areas in which the international community can support and enable moreeffective urban mitigation and adaptation responses:

1 Financial resources need to be made more directly available to local players – for example,for climate change adaptation in vulnerable cities, investment in a portfolio of alternativeenergy options, and investment resources for mitigation partnerships between localgovernments and local private-sector systems.

2 Bureaucratic burdens on local access to international support should be eased. The inter-national community can help to create direct communication and accountability channelsbetween local actors and international donors through intermediary organizations that canhelp disperse resources and monitor performance.

3 Information of climate change science and options for mitigation and adaptation responsesshould be more widely available. The Intergovernmental Panel on Climate Change (IPCC),the United Nations and other international organizations need to widen the spectrum ofavailable knowledge on observed and future climate change impacts upon urban centres;on mitigation and adaptation alternatives available for urban responses; and on the costs,benefits, potentials and limits of these options.

sets of policy and market conditions and rules that shapedecentralized activities – incentives, limits and expectationsfor the future – and by helping to coordinate responses thatinvolve a wide range of individual partners. They also playessential roles in looking beyond current conditions andpriorities, both for countries as a whole and cities in particu-lar, towards longer-term changes in conditions and thepossible need for changes in rules that define developmentpathways and risk management ‘playing fields’ (see also Box7.2):

• Enabling framework. National (and local) governmentsshould facilitate the climate change mitigation andadaptation interventions of all stakeholders. Theexample of the Philippines (see Box 6.3) illustrates howgovernments, through the provision of an enablingframework, can enhance the effectiveness of interven-tions of other actors, particularly people living inpoverty.

• Incentives. Some countries already offer incentives forclimate change mitigation actions, while manycountries, in effect, discourage mitigation and adapta-tion actions through policies enacted with other issuesin mind – or during earlier periods before climatechange became a reality. Countries can promote urbanarea initiatives related to climate change mitigation oradaptation by removing ‘maladaptations’ that arecounterproductive and by providing incentives such asfavourable tax treatment, eligibility for federal fundingsupport and high-visibility public recognition.

• Coordination. As cities, sectors, regions and otherparties act to support mitigation and adaptation, thesedispersed activities need coordination in order toensure that they are mutually reinforcing rather thancausing problems in other contexts. For example, adecision to convert a natural forest area to a bioenergyplantation can contribute to mitigation by reducing theneed for fossil fuels, but it can threaten biodiversityprotection. A decision by one city to protect coastalareas with barriers can have impacts upon wetlandecologies that are important to the economic base ofother cities inland. Countries should make it standardpolicy to ensure information-sharing about localizedplans and to provide mechanisms to resolve conflicts asthey arise.

• Risk-sharing. Countries can contribute to mitigation andadaptation by cities in two ways related to risk-sharing.On the adaptation side, a frequent concern is withclimate change threats that have high probabilities ofoccurring at a national level but low probabilities for anysingle city, such as extreme weather events. Here,countries can work together with private, non-governmental (such as slum federations) and publicproviders of insurance and reinsurance to offer protec-tion to each city without requiring each to make asizeable investment in order to reduce risks from aparticular kind of low-probability threat. On the mitiga-tion side, some possible actions involve technologiesthat are so innovative that their economic value has not

yet been fully established. Here, countries can encour-age innovation through such policies as offering partialloan guarantees in case the technology does notperform as well as hoped.

• Assistance where transformational adaptations arerequired. Countries should help their cities in lookingahead to the possibilities of much more substantialclimate change impacts and adaptation needs in thelonger term than those that are currently anticipated inthe next decades. An example might be a city located ina vulnerable coastal area subject to threats from moresevere storms and sea-level rise over the next halfcentury, where in the longer run, moving some popula-tions and economic activities away from the mostvulnerable areas might need to be considered. Asindicated earlier in this chapter, policies should supportcontingency planning, monitoring of emerging condi-tions and the development of response alternatives.

City policies

Urban areas are the main loci of action, rooted in local devel-opment aspirations and preferences, local knowledge ofneeds and options, local awareness of realities that shapechoices, and local potentials for innovation. One of the majorchallenges for policies in most urban areas, however, is tobroaden the discourse about policy directions beyondconventional structures of political power and governmentaction, and to engage their communities much more inclu-sively (see Chapter 5). With this challenge in mind, urbanpolicies should (see also Box 7.3):

As cities, sectors,regions and otherparties act tosupport mitigationand adaptation,these dispersedactivities needcoordination


Box 7.2 Key principles for urban climate change policy development: National governments

National governments should primarily use the following mechanisms to enable mitigation andadaptation actions at the local level:

• Engage in the design and implementation of national mitigation strategies and adaptationplanning.

• Offer tax rebates, tax exemptions and other incentives for investments in alternativeenergy sources, energy-efficient appliances, climate-proof infrastructures, houses and appli-ances, among other climate change mitigation and adaptation actions.

• Encourage appropriate climate responses. For example, redesign policies enacted withother issues in mind or during periods prior to climate change, such as policies that usethe definition of a 100-year floodplain, which can result in maladaptations.

• Enhance coordination and streamlining between sectoral and administrative entities. Forinstance, make sure that decisions by one city to protect coastal areas with barriers do nothave impacts upon basins that are suppliers of fresh water, or wetland ecologies that areimportant to the economic base of that city or other cities inland.

• Develop partnerships with non-governmental actors to share risks (see also Box 7.4). Forexample, national governments can work with private insurance providers to offer protec-tion to each city without requiring each to make a sizeable investment in order to reducerisks from a particular kind of low-probability threat.

• Anticipate and plan for the possibility of much more substantial climate change impactsand adaptation needs in the longer term than those that are currently anticipated in thenext decades.

• Develop a vision of the future. A city is not in a positionto evaluate how climate change responses relate to itsurban development unless it has a vision of where itwants that development to go. This requires not onlythe development of possible scenarios of futureeconomic, demographic and land-use futures, alongwith resource requirements, but also richer ‘narratives’of a set of futures that help to explain why they aredesirable from the city’s perspective.

• Expand the scope of community participation and action.In connection with developing its vision, a city needs tobecome a community of communities – reachingbeyond formal governmental structures to the privatesector, neighbourhoods and grassroots groups, as wellas opinion leaders of all kinds in order to ensure abroad-based collection of perspectives is gathered. Thisis crucial for ensuring knowledge, innovation and broad-based support for a city’s response strategy (seeChapter 6).

• Conduct participatory risk assessments and turn theassessments into action plans. Using inclusive participa-tory processes, in which both women and men, as wellas all socio-economic and age groups are represented,supplemented by scientific knowledge, cities shouldassess risks to their urban development plans and objec-tives, identify ways to reduce those risks throughactions in the near term that offer development co-benefits, develop a plan of action to take high-priorityactions, and consider longer-term risks that may requirelarger-scale planning and strategy development (seeChapter 6).

• Pay particular attention to the importance of investmentin major infrastructure. Major infrastructure casts longshadows through time for both mitigation and adapta-tion. Particularly important is investment in small- andmedium-sized urban centres, including in large residen-tial and commercial developments, governmentstructures, industrial structures, transportationsystems, energy facilities, and other facilities such aswater supply and waste disposal systems. The time toconsider mitigation and adaptation is when these typesof infrastructure are being designed, when the cost ofclimate-sensitive features is almost always smaller thanafter the infrastructure is in place. An example of apolicy option in vulnerable coastal or riverine citieswould be a building code for new infrastructure devel-opments that requires them to be able to withstandsignificant future flooding.

Policies of other partners in a global policy response

Governments do not, in isolation, determine appropriateresponses to climate change in development contexts. Theprivate sector and NGOs are critically important partners.Other organizations may be important in some urban areasas well, such as community and/or faith-based organizations(see also Box 7.4):


Box 7.3 Key principles for urban climate change policy development: Local authorities

Urban policy-makers should begin from an awareness of local development aspirations andpreferences, local knowledge of needs and options, local realities that shape choices, and localpotentials for innovation. Urban authorities should:

• Develop a vision of where they want their future development to go and find ways ofrelating climate change responses to urban development aspirations.

• Expand the scope of community participation and action by representatives of the privatesector, neighbourhoods (especially the poor) and grassroots groups, as well as opinionleaders of all kinds in order to ensure that a broad-based collection of perspectives isgathered.

• Using an inclusive participatory process (as referred to above), cities should conductvulnerability assessments to identify common and differentiated risks to their urban devel-opment plans and their different demographic sectors, and decide on objectives and waysto reduce those risks.

• Pay particular attention to the importance of adding climate-sensitive features to majorinfrastructure, especially when they are being designed, as the cost of adding these featureswill almost always be smaller before the infrastructure is built than they would after it is inplace.

Box 7.4 Key principles for urban climate change policy development: Other partners

In order to achieve more effective policies, local governments need to expand the scope,accountability and effectiveness of participation and engagement of NGOs, such as communityand grassroots groups, the academic sector, the private sector and opinion leaders. This willserve multiple purposes:

• It will become a source of innovative options, as well as both scientific and locally relevantknowledge.

• It will allow participants to understand and mediate the diverse perspectives and interestsat play.

• It will provide a broad-based support for decisions and promote knowledge on the causesof emissions and vulnerabilities, as well as mitigation and adaptation options thus achieved.

Partnerships with the private sector and NGOs are of special relevance in this context. Forexample:

• Resources from international, national and local private organizations can be mobilized toinvest in the development of new technologies, housing projects and climate-proof infra-structures, and to aid in the development of climate change risk assessments.

• The widespread involvement of NGOs in climate arenas as diverse as climate awarenessand education and disaster relief should be welcomed rather than making attempts tokeep them outside of these structures and interactions. The inputs and perspectives ofthese organizations can be harnessed to help develop a more integrated urban develop-ment planning.

Broad-based oversight organizations, such as advisory boards, representing the interests of allactors should be created to help avoid the danger that private or sectarian interests maydistort local action – for instance, by investing in technologies, infrastructures and housing thatonly benefit a minority, or by hijacking the benefits of grassroots funding. This is especially ofconcern in urban areas within countries that have experienced strong centralized control in thehands of local elites and state agents; but the principle of broad-based oversight can and shouldbe practised everywhere.

• The private sector. Positive connections between climatechange responses and urban development will onlybecome mainstreamed when they become part ofnormal day-to-day decision-making in local markets andlocal economic institutions. Ranging from activities oflarge multinational corporations to local informal indus-tries, the private sector must be included in urban,national and global policy-making on climate-relatedissues. For localities, this starts with including theprivate sector in discussions of urban needs and alterna-tives; encouraging private-sector organizations toconduct their own climate change risk assessments;looking for roles that they can play better than thepublic sector (such as stockpiling and providingemergency supplies); and encouraging innovative think-ing about how private-sector business strategies canfind opportunities in helping cities strengthen theircommitments to climate change mitigation and adapta-tion.

• Non-governmental organizations. NGOs range frominternational environmental groups that provide infor-mation, technical assistance and policy advocacy;philanthropic foundations that take the lead in develop-ing urban climate change response initiatives whengovernments and the private sector prove unwilling tomove ahead quickly enough; and local communityorganizations, formal and informal, that play major rolesin emergency response situations in cities – and arestepping forward to represent the interests andconcerns of especially vulnerable populations in manycities. Here, the policy challenge is to incorporate theseroles within integrated urban development planningrather than hold them outside these structures andinteractions.

CONCLUDING REMARKSIn summary, policy directions for linking climate changeresponses with urban development offer abundant opportu-nities; but they call for new philosophies about how to thinkabout the future and how to connect different roles of differ-ent levels of government and different parts of the urbancommunity. In many cases, this implies changes in howurban areas operate – fostering closer coordination betweenlocal governments and local economic institutions, andbuilding new connections between central power structuresand parts of the population who have often been keptoutside of the circle of consultation and discourse.

The difficulties involved in changing deeply setpatterns of interaction and decision-making in urban areasshould not be underestimated. Because it is so difficult,successful experiences need to be identified, described andwidely publicized as models for others. However, where thischallenge is met, it is likely not only to increase opportuni-ties and reduce threats to urban development in profoundlyimportant ways, but to make the urban area a more effectivesocio-political entity, in general – a better city in how itworks day to day and how it solves a myriad of problems asthey emerge – far beyond climate change connections alone.

It is in this sense that climate change responses canbe catalysts for socially inclusive, economically productiveand environmentally friendly urban development, helping topioneer new patterns of stakeholder communication andparticipation.50

1 I.e. the Annex 1 countries ofthe UNFCCC; see Chapter 2.

2 UN, 2010.3 UN, 2010.4 The Adaptation Fund only

became operational in 2010.See also Boxes 2.2 and 2.3.

5 However, and as noted earlier,an International Standard forDetermining Greenhouse GasEmissions for Cities waslaunched by UNEP, UN-Habitatand the World Bank at theWorld Urban Forum in Rio deJaneiro, Brazil, in March 2010.

6 It should, however, be notedthat the provision of modernsanitation facilities becomesless expensive with densifica-tion.

7 Such as housing co-operativesin Tel Aviv, Israel (see Chapter5).

8 Such as the Project 2° (seeChapter 5).

9 See Chapter 1.

10 Such as Denver andWashington, DC (see Chapter3).

11 See Chapter 5.12 See Chapter 5.13 See Box 5.4.14 In line with the activities and

recommendations of the C40and ICLEI (see Chapters 2 and5).

15 See Chapter 5.16 See Chapters 2 and 5.17 See Chapter 2.18 Sims et al, 2007.19 Through the CDM (see Box

2.3) and through suchprogrammes as the UnitedNations CollaborativeProgramme on ReducingEmissions from Deforestationand Forest Degradation inDeveloping Countries (UN-REDD) (see Table 2.2).

20 See Chapter 2.21 See Chapter 6.22 See Chapters 4 and 6.

23 See Chapter 6.24 See NRC, 2010.25 NRC, 2009, 2010; Greene et al,

2010.26 ‘Decarbonized’ as a result of

carbon capture and storageinitiatives (see Chapter 5).

27 See Chapter 3.28 Barker et al, 2007.29 See Chapter 5.30 See Chapter 2.31 Barker et al, 2007.32 See Chapter 5.33 Barker et al, 2007.34 See Chapters 4 and 6.35 ACIA, 2004.36 See Chapter 6.37 This having been said, it is

important to note that someclimate change adaptationinterventions can be verycostly and/or contentious.

38 See Chapter 6.39 See Chapter 6.40 NRC, 2010.41 Wilbanks and Sathaye, 2007.

42 Such as in Beijing (China) (seeChapter 5).

43 See Chapter 5.44 See Chapter 5.45 NRC, 2010.46 See, for example, Rosenzweig

et al, 2011.47 See Chapter 5.48 Wilbanks, 2007.49 The proposal was submitted by

the World Bank in July 2010.Under present rules, the CDMExecutive Board cannotapprove programmes of activi-ties that use multiplemethodologies. By their verynature, city-wide programmesdraw on a range of methodolo-gies that support GHGmitigation technologies; but assuch they cannot be consid-ered for approval through theCDM – unless the guidelines ofthe CDM Executive Board arerevised.

50 Wilbanks, 2003.


NOTES

Climate changeresponses can becatalysts for sociallyinclusive, economically productive andenvironmentallyfriendly urban development

GENERAL DISCLAIMERThe designations employed and presentation of the data do not imply theexpression of any opinion whatsoever on the part of the Secretariat of theUnited Nations concerning the legal status of any country, city or area orof its authorities, or concerning the delimitation of its frontiers or bound-aries.

STATISTICAL ANNEX

The Statistical Annex comprises 16 tables covering suchbroad statistical categories as demography, housing,economic and social indicators. The Annex is divided intothree sections presenting data at the regional, country andcity levels. Tables A.1 to A.4 present regional-level datagrouped by selected criteria of economic and developmentachievements, as well as geographic distribution. Tables B.1to B.8 contain country-level data and Tables C.1 to C.3 aredevoted to city-level data. Data have been compiled fromvarious international sources, from national statistical officesand from the United Nations.

EXPLANATION OF SYMBOLSThe following symbols have been used in presenting datathroughout the Statistical Annex:

category not applicable ..data not available …magnitude zero –

COUNTRY GROUPINGS ANDSTATISTICAL AGGREGATESWorld major groupings

More developed regions: All countries and areas of Europeand Northern America, as well as Australia, Japan and NewZealand.

Less developed regions: All countries and areas of Africa,Latin America, Asia (excluding Japan) and Oceania (exclud-ing Australia and New Zealand).

Least developed countries: Afghanistan, Angola,Bangladesh, Benin, Bhutan, Burkina Faso, Burundi,Cambodia, Central African Republic, Chad, Comoros,Democratic Republic of the Congo, Djibouti, EquatorialGuinea, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau,Haiti, Kiribati, Lao People’s Democratic Republic, Lesotho,Liberia, Madagascar, Malawi, Maldives, Mali, Mauritania,Mozambique, Myanmar, Nepal, Niger, Rwanda, Samoa, São

Tomé and Príncipe, Senegal, Sierra Leone, Solomon Islands,Somalia, Sudan, Timor-Leste, Togo, Tuvalu, Uganda, UnitedRepublic of Tanzania, Vanuatu, Yemen, Zambia.

Small Island Developing States:1 American Samoa,Anguilla, Antigua and Barbuda, Aruba, Bahamas, Bahrain,Barbados, Belize, British Virgin Islands, Cape Verde,Comoros, Cook Islands, Cuba, Dominica, DominicanRepublic, Fiji, French Polynesia, Grenada, Guam, Guinea-Bissau, Guyana, Haiti, Jamaica, Kiribati, Maldives, MarshallIslands, Mauritius, Micronesia (Federated States of),Montserrat, Nauru, Netherlands Antilles, New Caledonia,Niue, Northern Mariana Islands, Palau, Papua New Guinea,Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincentand the Grenadines, Samoa, São Tomé and Príncipe,Seychelles, Solomon Islands, Suriname, Timor-Leste, Tonga,Trinidad and Tobago, Tuvalu, United States Virgin Islands,Vanuatu.

Sub-Saharan Africa: Angola, Benin, Botswana, BurkinaFaso, Burundi, Cameroon, Cape Verde, Central AfricanRepublic, Chad, Comoros, Congo, Côte d’Ivoire, DemocraticRepublic of the Congo, Djibouti, Egypt, Equatorial Guinea,Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali,Mauritania, Mauritius, Mayotte, Morocco, Mozambique,Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, SãoTomé and Príncipe, Senegal, Seychelles, Sierra Leone,Somalia, South Africa, Sudan, Swaziland, Togo, Uganda,United Republic of Tanzania, Zambia, Zimbabwe.

Countries in the Human Development Indexaggregates2

Very high human development: Andorra, Australia,Austria, Bahrain, Barbados, Belgium, Brunei Darussalam,Canada, Cyprus, Czech Republic, Denmark, Estonia, Finland,France, Germany, Greece, Hong Kong SAR of China,Hungary, Iceland, Ireland, Israel, Italy, Japan, Liechtenstein,Luxembourg, Malta, Netherlands, New Zealand, Norway,Poland, Portugal, Qatar, Republic of Korea, Singapore,Slovakia, Slovenia, Spain, Sweden, Switzerland, United ArabEmirates, United Kingdom, United States of America.

TECHNICAL NOTES

High human development: Albania, Algeria, Argentina,Armenia, Azerbaijan, Bahamas, Belarus, Belize, Bosnia andHerzegovina, Brazil, Bulgaria, Chile, Colombia, Costa Rica,Croatia, Ecuador, Georgia, Iran (Islamic Republic of),Jamaica, Jordan, Kazakhstan, Kuwait, Latvia, Libyan ArabJamahiriya, Lithuania, Malaysia, Mauritius, Mexico,Montenegro, Panama, Peru, Romania, Russian Federation,Saudi Arabia, Serbia, The former Yugoslav Republic ofMacedonia, Tonga, Trinidad and Tobago, Tunisia, Turkey,Ukraine, Uruguay, Venezuela (Bolivarian Republic of).

Medium human development: Bolivia, Botswana,Cambodia, Cape Verde, China, Congo, Dominican Republic,Egypt, El Salvador, Equatorial Guinea, Fiji, Gabon,Guatemala, Guyana, Honduras, India, Indonesia, Kyrgyzstan,Lao People’s Democratic Republic, Maldives, Micronesia(Federated States of), Moldova, Mongolia, Morocco,Namibia, Nicaragua, Pakistan, Paraguay, Philippines, SãoTomé and Príncipe, Solomon Islands, South Africa, Sri Lanka,Suriname, Swaziland, Syrian Arab Republic, Tajikistan,Thailand, Timor-Leste, Turkmenistan, Uzbekistan, Viet Nam.

Low human development: Afghanistan, Angola,Bangladesh, Benin, Burkina Faso, Burundi, Cameroon,Central African Republic, Chad, Comoros, Côte d’Ivoire,Democratic Republic of the Congo, Djibouti, Ethiopia,Gambia, Ghana, Guinea, Guinea-Bissau, Haiti, Kenya,Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania,Mozambique, Myanmar, Nepal, Niger, Nigeria, Papua NewGuinea, Rwanda, Senegal, Sierra Leone, Sudan, Togo,Uganda, United Republic of Tanzania, Yemen, Zambia,Zimbabwe.

Countries in the income aggregates3

The World Bank classifies all member economies and allother economies with populations of more than 30,000. Inthe World Development Report 2011, economies are dividedamong income groups according to 2009 GNI per capita,calculated using the World Bank Atlas method. The groupsare:

High income: Andorra, Aruba, Australia, Austria, Bahamas,Bahrain, Barbados, Belgium, Bermuda, Brunei Darussalam,Canada, Cayman Islands, Channel Islands, Croatia, Cyprus,Czech Republic, Denmark, Equatorial Guinea, Estonia,Faeroe Islands, Finland, France, French Polynesia, Germany,Gibraltar, Greece, Greenland, Guam, Hong Kong SAR ofChina, Hungary, Iceland, Ireland, Isle of Man, Israel, Italy,Japan, Kuwait, Latvia, Liechtenstein, Luxembourg, MacaoSAR of China, Malta, Monaco, Netherlands Antilles,Netherlands, New Caledonia, New Zealand, NorthernMariana Islands, Norway, Oman, Poland, Portugal, PuertoRico, Qatar, Republic of Korea, San Marino, Saudi Arabia,Singapore, Slovakia, Slovenia, Spain, Sweden, Switzerland,Trinidad and Tobago, Turks and Caicos Islands, United ArabEmirates, United Kingdom, United States of America, UnitedStates Virgin Islands.

Upper-middle income: Albania, Algeria, American Samoa,Antigua and Barbuda, Argentina, Azerbaijan, Belarus, Bosniaand Herzegovina, Botswana, Brazil, Bulgaria, Chile,Colombia, Costa Rica, Cuba, Dominica, Dominican Republic,Fiji, Gabon, Grenada, Iran (Islamic Republic of), Jamaica,Kazakhstan, Lebanon, Libyan Arab Jamahiriya, Lithuania,Malaysia, Mauritius, Mayotte, Mexico, Montenegro,Namibia, Palau, Panama, Peru, Romania, Russian Federation,Serbia, Seychelles, South Africa, Saint Kitts and Nevis, SaintLucia, Saint Vincent and the Grenadines, Suriname, Theformer Yugoslav Republic of Macedonia, Turkey, Uruguay,Venezuela (Bolivarian Republic of).

Lower-middle income: Angola, Armenia, Belize, Bhutan,Bolivia, Cameroon, Cape Verde, China, Congo, Côte d’Ivoire,Djibouti, Ecuador, Egypt, El Salvador, Georgia, Guatemala,Guyana, Honduras, India, Indonesia, Iraq, Jordan, Kiribati,Lesotho, Maldives, Marshall Islands, Micronesia (FederatedStates of), Moldova, Mongolia, Morocco, Nicaragua, Nigeria,Occupied Palestinian Territory, Pakistan, Papua New Guinea,Paraguay, Philippines, Samoa, São Tomé and Príncipe,Senegal, Sri Lanka, Sudan, Swaziland, Syrian Arab Republic,Thailand, Timor-Leste, Tonga, Tunisia, Turkmenistan, Tuvalu,Ukraine, Uzbekistan, Vanuatu, Viet Nam, Yemen.

Low income: Afghanistan, Bangladesh, Benin, Burkina Faso,Burundi, Cambodia, Central African Republic, Chad,Comoros, Democratic People’s Republic of Korea,Democratic Republic of the Congo, Eritrea, Ethiopia,Gambia, Ghana, Guinea, Guinea-Bissau, Haiti, Kenya,Kyrgyzstan, Lao People’s Democratic Republic, Liberia,Madagascar, Malawi, Mali, Mauritania, Mozambique,Myanmar, Nepal, Niger, Rwanda, Sierra Leone, SolomonIslands, Somalia, Tajikistan, Togo, Uganda, United Republicof Tanzania, Zambia, Zimbabwe.

Sub-regional aggregates

n AfricaEastern Africa: Burundi, Comoros, Djibouti, Eritrea,Ethiopia, Kenya, Madagascar, Malawi, Mauritius, Mayotte,Mozambique, Réunion, Rwanda, Seychelles, Somalia,Uganda, United Republic of Tanzania, Zambia, Zimbabwe.Middle Africa: Angola, Cameroon, Central AfricanRepublic, Chad, Congo, Democratic Republic of the Congo,Equatorial Guinea, Gabon, São Tomé and Príncipe.Northern Africa: Algeria, Egypt, Libyan Arab Jamahiriya,Morocco, Sudan, Tunisia, Western Sahara.Southern Africa: Botswana, Lesotho, Namibia, SouthAfrica, Swaziland.Western Africa: Benin, Burkina Faso, Cape Verde, Côted’Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia,Mali, Mauritania, Niger, Nigeria, Saint Helena, Senegal,Sierra Leone, Togo.

n AsiaEastern Asia: China, Hong Kong SAR of China, Macao SARof China, Democratic People’s Republic of Korea, Japan,Mongolia, Republic of Korea.


South-Central Asia: Afghanistan, Bangladesh, Bhutan,India, Iran (Islamic Republic of), Kazakhstan, Kyrgyzstan,Maldives, Nepal, Pakistan, Sri Lanka, Tajikistan,Turkmenistan, Uzbekistan.South-Eastern Asia: Brunei Darussalam, Cambodia,Indonesia, Lao People’s Democratic Republic, Malaysia,Myanmar, Philippines, Singapore, Thailand, Timor-Leste,Viet Nam.Western Asia: Armenia, Azerbaijan, Bahrain, Cyprus,Georgia, Iraq, Israel, Jordan, Kuwait, Lebanon, OccupiedPalestinian Territory, Oman, Qatar, Saudi Arabia, Syrian ArabRepublic, Turkey, United Arab Emirates, Yemen.

n EuropeEastern Europe: Belarus, Bulgaria, Czech Republic,Hungary, Moldova, Poland, Romania, Russian Federation,Slovakia, Ukraine.Northern Europe: Channel Islands, Denmark, Estonia,Faeroe Islands, Finland, Iceland, Ireland, Isle of Man, Latvia,Lithuania, Norway, Sweden, United Kingdom.Southern Europe: Albania, Andorra, Bosnia andHerzegovina, Croatia, Gibraltar, Greece, Holy See, Italy,Malta, Montenegro, Portugal, San Marino, Serbia, Slovenia,Spain, The former Yugoslav Republic of Macedonia.Western Europe: Austria, Belgium, France, Germany,Liechtenstein, Luxembourg, Monaco, Netherlands,Switzerland.

n Latin America and the CaribbeanCaribbean: Anguilla, Antigua and Barbuda, Aruba, Bahamas,Barbados, British Virgin Islands, Cayman Islands, Cuba,Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti,Jamaica, Martinique, Montserrat, Netherlands Antilles,Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincentand the Grenadines, Trinidad and Tobago, Turks and CaicosIslands, United States Virgin Islands.Central America: Belize, Costa Rica, El Salvador,Guatemala, Honduras, Mexico, Nicaragua, Panama.South America: Argentina, Bolivia, Brazil, Chile, Colombia,Ecuador, Falkland Islands (Malvinas), French Guiana,Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela(Bolivarian Republic of).

n Northern AmericaBermuda, Canada, Greenland, Saint-Pierre-et-Miquelon,United States of America.

n OceaniaAustralia/New Zealand: Australia, New Zealand.Melanesia: Fiji, New Caledonia, Papua New Guinea,Solomon Islands, Vanuatu.Micronesia: Guam, Kiribati, Marshall Islands, Micronesia(Federated States of), Nauru, Northern Mariana Islands,Palau.Polynesia: American Samoa, Cook Islands, French Polynesia,Niue, Pitcairn, Samoa, Tokelau, Tonga, Tuvalu, Wallis andFutuna Islands.

NOMENCLATURE ANDORDER OF PRESENTATIONTables A.1 to A.4 contain regional data, grouped in income,human development and geographic aggregates. Tables B.1to B.8 and C.1 to C.3 contain country and city-level data,respectively. In these tables, the countries or areas are listedin English alphabetical order within the macro-regions ofAfrica, Asia, Europe, Latin America, Northern America andOceania. Countries or area names are presented in the formcommonly used within the United Nations Secretariat forstatistical purposes. Due to space limitations, the short nameis used – for example, the United Kingdom of Great Britainand Northern Ireland is referred to as ‘United Kingdom’.

DEFINITION OF TERMS

Access to electricity: percentage of households which,within their housing unit are connected to electricity.

Access to piped water: percentage of households which,for source of drinking water are connected to piped waterwithin their housing unit, tap placed in the yard or plotoutside the house.

Access to sewerage: percentage of households which,within their housing unit are connected to sewerage.

Access to telephone: percentage of households which,within their housing unit are connected to telephone.

Access to mobile: percentage of households with mobilephone.

Gini index: the extent to which the distribution of income(or, in some cases, consumption expenditure) or assets (suchas land) among individuals or households within an economydeviates from a perfectly equal distribution. A Lorenz curveplots the cumulative percentages of total income receivedagainst the cumulative number of recipients, starting withthe poorest individual or household. The Gini indexmeasures the area between the Lorenz curve and ahypothetical line of absolute equality, expressed as apercentage of the maximum area under the line. Thus, a Giniindex of 0 represents perfect equality, while an index of 1implies absolute inequality.

Greenhouse gas emissions, carbon dioxide: emissionsfrom the burning of fossil fuels and the manufacture ofcement and include carbon dioxide produced during theconsumption of solid, liquid, and gas fuels and gas flaring.

Greenhouse gas emissions, methane: emissions fromhuman activities such as agriculture and from industrialmethane production.

Greenhouse gas emissions, nitrous oxide: emissions fromagricultural biomass burning, industrial activities, andlivestock management.

Greenhouse gas emissions, other: the by-productemissions of hydrofluorocarbons (by-product emissions offluoroform from chlorodifluoromethane manufacture and

189Technical Notes

use of hydrofluorocarbons), perfluorocarbons (by-productemissions of tetrafluoromethane and hexafluoroethane fromprimary aluminium production and use of fluorocarbons, inparticular for semiconductor manufacturing), and sulphurhexafluoride (various sources, the largest being the use andmanufacture of gas insulated switchgear used in electricitydistribution networks).

Greenhouse gas emissions, percentage change: (calcu-lated by UN-Habitat) refers to the average annual percentagegrowth rate of metric tonnes of emissions produced duringthe indicated period for each country, major regions andglobal totals.

Gross national income: the sum of value added by allresident producers plus any product taxes (less subsidies)not included in the valuation of output plus net receipts ofprimary income (compensation of employees and propertyincome) from abroad. Data are in current US dollarsconverted using the World Bank Atlas method.

Gross national income per capita: gross national income(GNI) divided by mid-year population. GNI per capita in USdollars is converted using the World Bank Atlas method.

Gross national income PPP: gross national incomeconverted to international dollars using purchasing powerparity (PPP) rates. An international dollar has the samepurchasing power over GNI as a US dollar has in the UnitedStates of America.

Household: the concept of household is based on thearrangements made by persons, individually or in groups, forproviding themselves with food or other essentials for living.A household may be either:

1. A one-person household: a person who makes provisionfor his or her own food or other essentials for livingwithout combining with any other person to form a partof a multi-person household.

2. A multi-person household: a group of two or morepersons living together who make common provision forfood or other essentials for living. The persons in thegroup may pool their incomes and may, to a greater orlesser extent, have a common budget; they may berelated or unrelated persons or constitute a combinationof persons both related and unrelated. This concept ofhousehold is known as the ‘housekeeping’ concept. Itdoes not assume that the number of households andhousing units is equal. Although the concept of housingunit implies that it is a space occupied by one house-hold, it may also be occupied by more than onehousehold or by a part of a household (e.g. two nuclearhouseholds that share one housing unit for economicreasons or one household in a polygamous societyroutinely occupying two or more housing units).

Household connection to improved drinking water:percentage of households which, within their housing unit,are connected to any of the following types of water supplyfor drinking: piped water, public tap, borehole or pump,protected well, protected spring or rainwater.

Improved drinking water coverage: percentage of peopleusing improved drinking water sources or delivery points.Improved drinking water technologies are more likely toprovide safe drinking water than those characterized asunimproved. Improved drinking water sources: piped waterinto dwelling, plot or yard; public tap/standpipe; tube well/borehole; protected dug well; protected spring; rainwatercollection. Unimproved drinking water sources: unprotecteddug well; unprotected spring; cart with small tank/drum;bottled water;4 tanker-truck; surface water (river, dam, lake,pond, stream, canal, irrigation channels).

Improved sanitation coverage: percentage of people usingimproved sanitation facilities. Improved sanitation facilitiesare more likely to prevent human contact with humanexcreta than unimproved facilities.

International poverty line: based on nationally representa-tive primary household surveys conducted by nationalstatistical offices or by private agencies under the supervi-sion of government or international agencies and obtainedfrom government statistical offices and World Bank countrydepartments. Population below US$1.25 a day andpopulation below US$2 a day: percentages of the popula-tion living on less than $1.25 a day and $2 a day at 2005international prices. As a result of revisions in PPP exchangerates, poverty rates for individual countries cannot becompared with poverty rates reported in earlier editions

Level of urbanization: percentage of the population resid-ing in places classified as urban. Urban and rural settlementsare defined in the national context and vary among countries(the definitions of urban are generally national definitionsincorporated within the latest census).

Motor vehicles: include cars, buses and freight vehicles butnot two-wheelers.

National population below national poverty line:percentage of the country’s population living below thenational poverty line. National estimates are based onpopulation weighted subgroup estimates from householdsurveys.

Persons in housing units: number of persons resident inhousing units.

Population, rural: mid-year estimates and projections(medium variant) of the population residing in human settle-ments classified as rural (see also ‘Population, urban’ below).

Population, total: mid-year population estimates andprojections for the world, region, countries or areas. ThePopulation Division of the United Nations Department ofEconomic and Social Affairs updates, every two years,population estimates and projections by incorporating newdata, new estimates and new analyses of data on population,fertility, mortality and international migration. Data fromnew population censuses and/or demographic surveys areused to verify and update old estimates of population ordemographic indicators, or to make new ones and to checkthe validity of the assumptions made in the projections.Population rate of change (calculated by UN-Habitat) refers


to the average annual percentage change of populationduring the indicated period for each country, major regionsand global totals. The formula used throughout the Annex isas follows: r = [(1/t) � ln(A2/A1)] � 100, where ‘A1’ is avalue at any given year; ‘A2’ is a value at any given year laterthan the year of ‘Al’; ‘t’ is the year interval between ‘Al’ and‘A2’; and ‘ln’ is the natural logarithm function.

Population, urban: mid-year population of areas defined asurban in each country and reported to the United Nations.Estimates of the world’s urban population would changesignificantly if China, India, and a few other populousnations were to change their definition of urban centres.According to China’s State Statistical Bureau, by the end of1996 urban residents accounted for about 43 per cent ofChina’s population, while in 1994 only 20 per cent of thepopulation was considered urban. In addition to the continu-ous migration of people from rural to urban areas, one of themain reasons for this shift was the rapid growth in thehundreds of towns reclassified as cities in recent years.Because the estimates in the table are based on nationaldefinitions of what constitutes a city or metropolitan area,cross-country comparisons should be made with caution.

Population density: mid-year population divided by landarea in square kilometres.

Railways: length of railway route available for train service,irrespective of the number of parallel tracks. Passengerscarried by railway are the number of passengers transportedby rail multiplied by kilometres travelled. Goods hauled byrailway are the volume of goods transported by railway,measured in metric tons multiplied by kilometres travelled.

Roads: motorways, highways, main or national roads, andsecondary or regional roads. A motorway is a road speciallydesigned and built for motor vehicles that separates thetraffic flowing in opposite directions. Total road network:includes motorways, highways and main or national roads,secondary or regional roads, and all other roads in a country.Paved roads: roads surfaced with crushed stone (macadam)and hydrocarbon binder or bitumized agents, with concreteor with cobblestones, as a percentage of all of the country’sroads measured in length. Goods hauled by road are thevolume of goods transported by road vehicles, measured inmillions of metric tons multiplied by kilometres travelled.

Survey year: the year in which the underlying data werecollected.

Urban poverty rate: percentage of the urban populationliving below the national urban poverty line.

Urban slum dwellers: individuals residing in housing withone or more of the following conditions: inadequate drinkingwater; inadequate sanitation; poor structural quality/durabil-ity of housing; overcrowding; and insecurity of tenure.

Urban agglomerations and capital cities: the term ‘urbanagglomeration’ refers to the population contained within thecontours of a contiguous territory inhabited at urban densitylevels without regard to administrative boundaries. It usuallyincorporates the population in a city or town plus that in the

suburban areas lying outside of but being adjacent to the cityboundaries. Whenever possible, data classified according tothe concept of urban agglomeration are used. However,some countries do not produce data according to theconcept of urban agglomeration but use instead that ofmetropolitan area or city proper. If possible, such data areadjusted to conform to the concept of urban agglomeration.When sufficient information is not available to permit suchan adjustment, data based on the concept of city proper ormetropolitan area are used. The sources listed onlineindicate whether data were adjusted to conform to the urbanagglomeration concept or whether a different concept wasused. Table C.1 contains revised estimates and projectionsfor all urban agglomerations comprising 750,000 or moreinhabitants.

SOURCES OF DATAThe Statistical Tables have been compiled from the followingUN-Habitat databases:

United Nations Human Settlements Programme (UN-Habitat), Global Urban Indicators Database 2010

United Nations Human Settlements Programme (UN-Habitat), Urban Info 2010

In addition, various statistical publications from the UnitedNations and other international organizations have beenused. These include:

United Nations Development Programme (2010) HumanDevelopment Report 2010, New York,http://hdr.undp.org/en/reports/global/hdr2010/

United Nations, Department of Economic and Social Affairs,Population Division (2009), World Population Prospects:The 2008 Revision, New York

United Nations, Department of Economic and Social Affairs,Population Division (2010) World UrbanizationProspects: The 2009 Revision, United Nations, New York

World Bank (2005) World Development Indicators 2005,World Bank, Washington, DC

World Bank (2006) World Development Report 2006, WorldBank, Washington, DC

World Bank (2010) World Development Indicators 2010,World Bank, Washington, DC

World Bank (2010) World Development Indicators Onlinedatabase, http://data.worldbank.org/indicator

World Bank (2010) World Development Report 2011, WorldBank, Washington, DC

World Health Organization (WHO) and United NationsChildren’s Fund (UNICEF) Joint Monitoring Programmefor Water Supply and Sanitation (JMP) (2010) Progresson Sanitation and Drinking-Water 2010 Update, WHOand UNICEF, Geneva and New York, www.who.int/water_sanitation_health/publications/9789241563956/en/index.html

191Technical Notes

1. As classified by United NationsDepartment of Economic andSocial Affairs (UNDESA); seehttp://www.sidsnet.org/sids_list.html for detail.

2. As classified by the UnitedNations DevelopmentProgramme (UNDP); seeHuman Development Report2010 for detail. The followingcountries and territories werenot classified: American Samoa,Anguilla, Antigua and Barbuda,Aruba, Bermuda, Bhutan,British Virgin Islands, CaymanIslands, Channel Islands, Cook

Islands, Cuba, DemocraticPeople’s Republic of Korea,Dominica, Eritrea, FaeroeIslands, Falkland Islands(Malvinas), French Guiana,French Polynesia, Gibraltar,Greenland, Grenada,Guadeloupe, Guam, Holy See,Iraq, Isle of Man, Kiribati,Lebanon, Macao SAR of China,Marshall Islands, Martinique,Mayotte, Monaco, Montserrat,Nauru, Netherlands Antilles,New Caledonia, Niue,Northern Mariana Islands,Occupied Palestinian Territory,

Oman, Palau, Pitcairn, PuertoRico, Réunion, Saint Helena,Saint Kitts and Nevis, SaintLucia, Saint Vincent and theGrenadines, Saint-Pierre-et-Miquelon, Samoa, San Marino,Seychelles, Somalia, Tokelau,Turks and Caicos Islands,Tuvalu, United States VirginIslands, Vanuatu, Wallis andFutuna Islands, and WesternSahara.

3. As classified by the WorldBank; see World DevelopmentReport 2011 for detail. Thefollowing countries and terri-

tories were not classified:Anguilla, British Virgin Islands,Cook Islands, Falkland Islands(Malvinas), French Guiana,Guadeloupe, Holy See,Martinique, Montserrat, Nauru,Niue, Pitcairn, Réunion, SaintHelena, Saint-Pierre-et-Miquelon, Tokelau, Wallis andFutuna Islands, and WesternSahara.

4. Bottled water is consideredimproved only when thehousehold uses water from animproved source for cookingand personal hygiene.


NOTES

DATA TABLES

REGIONAL AGGREGATESTABLE A.1 Total Population Size, Rate of Change and Population Density

Estimates and projections Rate of change Population density ('000) (%) (people/km2)

2000 2010 2020 2030 2000–2010 2010–2020 2020–2030 2000 2030

WORLD 6,115,367 6,908,688 7,674,833 8,308,895 1.22 1.05 0.79 45 61World Major AggregatesMore Developed Regions 1,194,967 1,237,228 1,268,343 1,281,628 0.35 0.25 0.10 22 24Less Developed Regions 4,920,400 5,671,460 6,406,489 7,027,267 1.42 1.22 0.92 59 85Least Developed Countries 677,368 855,209 1,060,067 1,272,279 2.33 2.15 1.82 33 61Other Less Developed Countries 4,243,033 4,816,251 5,346,422 5,754,988 1.27 1.04 0.74 68 93Less Developed Regions, excluding China 3,646,339 4,309,696 4,967,045 5,556,003 1.67 1.42 1.12 50 76Small Island Developing States 52,809 59,642 66,205 72,097 1.22 1.04 0.85 42 58Sub-Saharan Africa 674,842 863,314 1,081,114 1,307,831 2.46 2.25 1.90 28 54

Human Development Index AggregatesVery High Human Development 993,772 1,055,971 1,101,353 1,129,453 0.61 0.42 0.25 31 35High Human Development 970,891 1,052,377 1,124,577 1,175,057 0.81 0.66 0.44 20 24Medium Human Development 3,190,507 3,597,308 3,967,424 4,239,713 1.20 0.98 0.66 117 155Low Human Development 871,324 1,099,018 1,360,204 1,626,493 2.32 2.13 1.79 38 71

Income AggregatesHigh Income 1,036,187 1,106,127 1,158,870 1,193,450 0.65 0.47 0.29 27 32Middle Income 4,387,508 4,939,256 5,452,303 5,845,635 1.18 0.99 0.70 55 73Upper-Middle Income 931,193 1,015,174 1,085,244 1,134,305 0.86 0.67 0.44 19 23Lower-Middle Income 3,456,315 3,924,082 4,367,059 4,711,330 1.27 1.07 0.76 109 148

Low Income 691,678 863,301 1,063,654 1,269,812 2.22 2.09 1.77 39 71Geographic AggregatesAfrica 819,462 1,033,043 1,276,369 1,524,187 2.32 2.12 1.77 27 50Eastern Africa 252,710 327,186 420,200 518,064 2.58 2.50 2.09 40 81Middle Africa 98,060 128,909 164,284 201,602 2.74 2.42 2.05 15 30Northern Africa 179,525 212,921 247,564 277,351 1.71 1.51 1.14 21 33Southern Africa 51,387 57,968 61,134 64,037 1.21 0.53 0.46 19 24Western Africa 237,781 306,058 383,187 463,133 2.52 2.25 1.89 39 75

Asia 3,698,296 4,166,741 4,596,256 4,916,701 1.19 0.98 0.67 116 154Eastern Asia 1,472,444 1,563,951 1,640,388 1,666,372 0.60 0.48 0.16 125 142South-Central Asia 1,518,322 1,780,473 2,028,786 2,231,846 1.59 1.31 0.95 141 207South-Eastern Asia 517,193 589,615 653,541 706,492 1.31 1.03 0.78 115 157Western Asia 190,336 232,702 273,541 311,991 2.01 1.62 1.32 39 65

Europe 726,568 732,759 732,952 723,373 0.08 0.00 -0.13 32 31Eastern Europe 304,088 291,485 281,511 268,320 -0.42 -0.35 -0.48 16 14Northern Europe 94,359 98,909 103,400 107,221 0.47 0.44 0.36 52 59Southern Europe 145,119 153,778 157,455 157,228 0.58 0.24 -0.01 110 119Western Europe 183,001 188,587 190,585 190,605 0.30 0.11 0.00 165 172

Latin America and the Caribbean 521,228 588,649 645,543 689,859 1.22 0.92 0.66 25 34Caribbean 38,650 42,312 45,470 47,922 0.91 0.72 0.53 165 205Central America 135,171 153,115 169,861 183,885 1.25 1.04 0.79 55 74South America 347,407 393,221 430,212 458,052 1.24 0.90 0.63 19 26

Northern America 318,654 351,659 383,384 410,204 0.99 0.86 0.68 15 19Oceania 31,160 35,838 40,329 44,572 1.40 1.18 1.00 4 5Australia/New Zealand 23,039 25,815 28,344 30,627 1.14 0.93 0.77 3 4Melanesia 7,010 8,778 10,613 12,452 2.25 1.90 1.60 13 23Micronesia 497 573 646 713 1.43 1.19 1.00 160 230Polynesia 614 672 727 779 0.90 0.78 0.69 73 93

Sources: United Nations Department of Economic and Social Affairs, Population Division (2009) World Urbanization Prospects: The 2008 Revision, United Nations, New York; United Nations Department of Economic and SocialAffairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York. Figures in regional, income or development aggregates are calculated on the basis of country/area level data fromTable B.1.

Note: Lists of countries/areas in aggregates are presented in the Technical Notes.


TABLE A.2Urban and Rural Population Size and Rate of Change

Urban population Rural population

Estimates and projections Rate of change Estimates and projections Rate of change(’000) (%) (’000) (%)

2000 2010 2020 2030 2000– 2010– 2020– 2000 2010 2020 2030 2000– 2010– 2020–2010 2020 2030 2010 2020 2030

WORLD 2,837,431 3,486,326 4,176,234 4,899,858 2.06 1.81 1.60 3,277,937 3,422,362 3,498,599 3,409,038 0.43 0.22 -0.26World Major AggregatesMore Developed Regions 869,233 929,851 988,130 1,036,550 0.67 0.61 0.48 325,734 307,377 280,214 245,078 -0.58 -0.93 -1.34Less Developed Regions 1,968,198 2,556,475 3,188,104 3,863,308 2.62 2.21 1.92 2,952,203 3,114,985 3,218,385 3,163,960 0.54 0.33 -0.17Least Developed Countries 167,181 249,442 366,150 519,537 4.00 3.84 3.50 510,186 605,767 693,917 752,742 1.72 1.36 0.81Other Less Developed Countries 1,801,016 2,307,033 2,821,954 3,343,771 2.48 2.01 1.70 2,442,016 2,509,218 2,524,468 2,411,218 0.27 0.06 -0.46Less Developed Regions, excluding China 1,508,061 1,913,018 2,393,054 2,949,063 2.38 2.24 2.09 2,138,278 2,396,678 2,573,992 2,606,941 1.14 0.71 0.13Small Island Developing States 27,682 33,269 39,014 44,839 1.84 1.59 1.39 25,118 26,374 27,197 27,260 0.49 0.31 0.02Sub-Saharan Africa 220,606 321,400 456,580 626,683 3.76 3.51 3.17 454,236 541,914 624,534 681,148 1.76 1.42 0.87

Human Development Index AggregatesVery High Human Development 743,983 818,351 882,751 936,113 0.95 0.76 0.59 249,794 237,620 218,604 193,339 -0.50 -0.83 -1.23High Human Development 698,381 797,979 890,670 965,152 1.33 1.10 0.80 272,506 254,397 233,904 209,900 -0.69 -0.84 -1.08Medium Human Development 1,090,497 1,436,933 1,794,395 2,170,060 2.76 2.22 1.90 2,100,009 2,160,379 2,173,029 2,069,654 0.28 0.06 -0.49Low Human Development 247,830 366,677 529,624 734,793 3.92 3.68 3.27 623,497 732,343 830,587 891,698 1.61 1.26 0.71

Income AggregatesHigh Income 774,391 855,606 926,830 986,780 1.00 0.80 0.63 259,682 247,945 229,084 203,462 -0.46 -0.79 -1.19Middle Income 1,887,460 2,378,715 2,887,033 3,403,810 2.31 1.94 1.65 2,500,044 2,560,546 2,565,274 2,441,817 0.24 0.02 -0.49Upper-Middle Income 666,588 766,942 856,953 929,145 1.40 1.11 0.81 264,603 248,234 228,293 205,152 -0.64 -0.84 -1.07Lower-Middle Income 1,220,872 1,611,773 2,030,080 2,474,665 2.78 2.31 1.98 2,235,441 2,312,312 2,336,981 2,236,665 0.34 0.11 -0.44

Low Income 173,725 249,727 359,728 506,362 3.63 3.65 3.42 517,957 613,576 703,930 763,447 1.69 1.37 0.81Geographic AggregatesAfrica 294,602 412,990 569,117 761,293 3.38 3.21 2.91 524,861 620,053 707,253 762,895 1.67 1.32 0.76Eastern Africa 52,641 77,194 116,130 172,766 3.83 4.08 3.97 200,069 249,992 304,070 345,298 2.23 1.96 1.27Middle Africa 36,486 55,592 81,493 112,727 4.21 3.82 3.24 61,574 73,318 82,791 88,875 1.75 1.22 0.71Northern Africa 85,656 108,912 137,341 167,876 2.40 2.32 2.01 93,868 104,009 110,224 109,475 1.03 0.58 -0.07Southern Africa 27,657 34,021 38,809 43,741 2.07 1.32 1.20 23,730 23,947 22,325 20,295 0.09 -0.70 -0.95Western Africa 92,162 137,271 195,344 264,182 3.98 3.53 3.02 145,620 168,787 187,843 198,951 1.48 1.07 0.57

Asia 1,360,900 1,757,314 2,168,798 2,598,358 2.56 2.10 1.81 2,337,395 2,409,427 2,427,458 2,318,343 0.30 0.07 -0.46Eastern Asia 594,676 784,688 940,684 1,061,980 2.77 1.81 1.21 877,768 779,263 699,704 604,392 -1.19 -1.08 -1.46South-Central Asia 447,425 571,112 733,039 936,279 2.44 2.50 2.45 1,070,897 1,209,360 1,295,746 1,295,567 1.22 0.69 0.00South-Eastern Asia 197,360 246,701 305,412 373,411 2.23 2.13 2.01 319,833 342,914 348,130 333,081 0.70 0.15 -0.44Western Asia 121,438 154,813 189,664 226,688 2.43 2.03 1.78 68,897 77,889 83,877 85,303 1.23 0.74 0.17

Europe 514,422 533,295 552,486 567,403 0.36 0.35 0.27 212,146 199,464 180,465 155,970 -0.62 -1.00 -1.46Eastern Europe 207,409 200,938 199,963 198,744 -0.32 -0.05 -0.06 96,679 90,546 81,548 69,575 -0.66 -1.05 -1.59Northern Europe 73,502 78,217 83,704 89,282 0.62 0.68 0.65 20,857 20,691 19,695 17,939 -0.08 -0.49 -0.93Southern Europe 95,015 104,209 111,664 117,473 0.92 0.69 0.51 50,104 49,569 45,791 39,755 -0.11 -0.79 -1.41Western Europe 138,495 149,931 157,155 161,904 0.79 0.47 0.30 44,506 38,656 33,430 28,701 -1.41 -1.45 -1.53

Latin America and the Caribbean 393,420 468,757 533,147 585,490 1.75 1.29 0.94 127,807 119,892 112,395 104,369 -0.64 -0.65 -0.74Caribbean 23,708 28,278 32,510 36,143 1.76 1.39 1.06 14,941 14,034 12,960 11,779 -0.63 -0.80 -0.96Central America 92,948 110,251 127,463 143,535 1.71 1.45 1.19 42,222 42,865 42,398 40,350 0.15 -0.11 -0.50South America 276,764 330,228 373,175 405,812 1.77 1.22 0.84 70,643 62,993 57,037 52,240 -1.15 -0.99 -0.88

Northern America 252,154 288,803 324,279 355,499 1.36 1.16 0.92 66,500 62,856 59,105 54,705 -0.56 -0.62 -0.77Oceania 21,932 25,167 28,406 31,816 1.38 1.21 1.13 9,227 10,671 11,924 12,756 1.45 1.11 0.67Australia/New Zealand 20,024 22,878 25,516 27,948 1.33 1.09 0.91 3,015 2,937 2,827 2,679 -0.26 -0.38 -0.54Melanesia 1,329 1,614 2,110 2,964 1.94 2.68 3.40 5,680 7,164 8,503 9,488 2.32 1.71 1.10Micronesia 326 390 454 523 1.80 1.52 1.40 171 183 191 191 0.69 0.45 -0.04Polynesia 253 285 325 380 1.20 1.31 1.58 361 387 402 399 0.69 0.38 -0.08

Sources: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York. Figures in regional, income or development aggregatesare calculated on the basis of country/area level data from Table B.2.


195Data Tables

TABLE A.3Urbanization

Level of urbanization

Estimates and projections Rate of change(%) (%)

2000 2010 2020 2030 2000–2010 2010–2020 2020–2030

WORLD 46.4 50.5 54.4 59.0 0.84 0.75 0.80World Major AggregatesMore Developed Regions 72.7 75.2 77.9 80.9 0.33 0.36 0.37Less Developed Regions 40.0 45.1 49.8 55.0 1.19 0.99 1.00Least Developed Countries 24.7 29.2 34.5 40.8 1.67 1.69 1.67Other Less Developed Countries 42.4 47.9 52.8 58.1 1.21 0.97 0.96Less Developed Regions, excluding China 41.4 44.4 48.2 53.1 0.71 0.82 0.97Small Island Developing States 52.4 55.8 58.9 62.2 0.62 0.55 0.54Sub-Saharan Africa 32.7 37.2 42.2 47.9 1.30 1.26 1.26

Human Development Index AggregatesVery High Human Development 74.9 77.5 80.2 82.9 0.35 0.34 0.33High Human Development 71.9 75.8 79.2 82.1 0.53 0.44 0.36Medium Human Development 34.2 39.9 45.2 51.2 1.56 1.24 1.24Low Human Development 28.4 33.4 38.9 45.2 1.60 1.54 1.49

Income AggregatesHigh Income 74.9 77.5 80.2 82.9 0.35 0.34 0.33Middle Income 43.0 48.2 53.0 58.2 1.13 0.95 0.95Upper-Middle Income 71.6 75.5 79.0 81.9 0.54 0.44 0.37Lower-Middle Income 35.3 41.1 46.5 52.5 1.51 1.24 1.22

Low Income 25.1 28.9 33.8 39.9 1.41 1.56 1.65Geographic AggregatesAfrica 36.0 40.0 44.6 49.9 1.06 1.09 1.13Eastern Africa 20.8 23.6 27.6 33.3 1.25 1.58 1.88Middle Africa 37.2 43.1 49.6 55.9 1.48 1.40 1.20Northern Africa 47.7 51.2 55.5 60.5 0.70 0.81 0.87Southern Africa 53.8 58.7 63.5 68.3 0.87 0.78 0.73Western Africa 38.8 44.9 51.0 57.0 1.46 1.28 1.12

Asia 36.8 42.2 47.2 52.8 1.36 1.12 1.13Eastern Asia 40.4 50.2 57.3 63.7 2.17 1.34 1.06South-Central Asia 29.5 32.1 36.1 42.0 0.85 1.19 1.49South-Eastern Asia 38.2 41.8 46.7 52.9 0.92 1.11 1.23Western Asia 63.8 66.5 69.3 72.7 0.42 0.41 0.47

Europe 70.8 72.8 75.4 78.4 0.28 0.35 0.40Eastern Europe 68.2 68.9 71.0 74.1 0.11 0.30 0.42Northern Europe 77.9 79.1 81.0 83.3 0.15 0.23 0.28Southern Europe 65.5 67.8 70.9 74.7 0.34 0.45 0.52Western Europe 75.7 79.5 82.5 84.9 0.49 0.37 0.30

Latin America and the Caribbean 75.5 79.6 82.6 84.9 0.54 0.36 0.27Caribbean 61.3 66.8 71.5 75.4 0.86 0.67 0.53Central America 68.8 72.0 75.0 78.1 0.46 0.41 0.39South America 79.7 84.0 86.7 88.6 0.53 0.32 0.21

Northern America 79.1 82.1 84.6 86.7 0.37 0.29 0.24Oceania 70.4 70.2 70.4 71.4 -0.02 0.03 0.13Australia/New Zealand 86.9 88.6 90.0 91.3 0.19 0.16 0.14Melanesia 19.0 18.4 19.9 23.8 -0.31 0.78 1.80Micronesia 65.6 68.1 70.4 73.3 0.37 0.33 0.41Polynesia 41.2 42.4 44.7 48.8 0.30 0.52 0.88

Sources: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York. Figures in regional, income or development aggregatesare calculated on the basis of country/area level data from Table B.3.



TABLE A.4Urban Agglomerations

Number of urban agglomerations Distribution of urban population by PopulationEstimates and projections size of agglomerations estimates and projections

(%) ('000)

2000 2010 2020 2000 2010 2020 2000 2010 2020

WORLD10 million or more 16 21 28 8.2 9.3 10.4 231,624 324,190 436,3085 to 10 million 28 33 43 6.9 6.7 7.0 195,644 233,827 290,4561 to 5 million 305 388 467 20.6 22.1 22.0 584,050 772,084 917,985500,000 to 1 million 402 516 608 9.6 10.2 10.2 273,483 355,619 425,329Fewer than 500,000 … … … 54.7 51.6 50.4 1,552,631 1,800,607 2,106,156

World Major AggregatesMore Developed Regions10 million or more 5 6 6 9.8 10.9 10.5 85,279 101,228 103,8345 to 10 million 5 7 9 4.2 4.9 5.9 36,472 45,595 58,6921 to 5 million 98 102 104 22.5 22.0 21.2 195,393 204,587 209,392500,000 to 1 million 117 126 132 9.1 9.1 9.1 78,818 84,750 89,863Fewer than 500,000 … … … 54.4 53.1 53.3 473,271 493,691 526,350

Less Developed Regions10 million or more 11 15 22 7.4 8.7 10.4 146,345 222,962 332,4745 to 10 million 23 26 34 8.1 7.4 7.3 159,172 188,232 231,7641 to 5 million 207 286 363 19.7 22.2 22.2 388,657 567,497 708,593500,000 to 1 million 285 390 476 9.9 10.6 10.5 194,664 270,868 335,466Fewer than 500,000 … … … 54.8 51.1 49.6 1,079,360 1,306,916 1,579,806

Least Developed Countries10 million or more 1 1 2 6.2 5.9 8.6 10,285 14,648 31,5095 to 10 million 1 2 6 3.4 5.6 10.0 5,611 13,926 36,7551 to 5 million 20 27 38 21.9 23.2 19.7 36,567 57,905 72,152500,000 to 1 million 19 28 34 7.7 8.1 6.4 12,915 20,269 23,438Fewer than 500,000 … … … 60.9 57.2 55.2 101,803 142,693 202,296

Other Less Developed Countries10 million or more 10 14 20 7.6 9.0 10.7 136,060 208,314 300,9655 to 10 million 22 24 28 8.5 7.6 6.9 153,561 174,306 195,0091 to 5 million 187 259 325 19.5 22.1 22.6 352,090 509,591 636,441500,000 to 1 million 266 362 442 10.1 10.9 11.1 181,749 250,599 312,028Fewer than 500,000 … … … 54.3 50.5 48.8 977,555 1,164,222 1,377,510

Less Developed Regions, excluding China10 million or more 10 13 17 8.8 10.1 11.2 133,121 194,002 267,5765 to 10 million 16 18 25 7.3 6.7 7.1 110,003 127,795 170,6611 to 5 million 156 207 250 19.3 21.3 20.7 291,625 408,322 496,275500,000 to 1 million 189 242 293 8.7 8.8 8.6 130,840 168,013 206,053Fewer than 500,000 … … … 55.9 53.1 52.3 842,473 1,014,887 1,252,489

Sub-Saharan Africa10 million or more — 1 2 — 3.3 5.9 — 10,578 26,9495 to 10 million 2 2 5 5.8 4.3 6.6 12,844 13,926 29,9311 to 5 million 28 40 55 23.4 26.1 24.8 51,706 83,765 113,394500,000 to 1 million 32 51 58 10.3 10.9 9.1 22,795 34,940 41,453Fewer than 500,000 … … … 60.4 55.4 53.6 133,262 178,191 244,853

Geographic AggregatesAfricaEastern Africa10 million or more — — — — — — — — —5 to 10 million — — 2 — — 8.9 — — 10,2961 to 5 million 9 10 14 26.5 26.6 23.0 13,929 20,519 26,686500,000 to 1 million 4 10 11 4.5 9.5 6.8 2,393 7,324 7,895Fewer than 500,000 … … … 69.0 63.9 61.4 36,318 49,351 71,254

Middle Africa10 million or more — — 1 — — 15.7 — — 12,7885 to 10 million 1 1 1 15.4 15.7 8.7 5,611 8,754 7,0801 to 5 million 3 7 9 14.3 25.3 20.5 5,216 14,087 16,712500,000 to 1 million 9 9 12 17.4 11.4 10.7 6,334 6,321 8,679Fewer than 500,000 … … … 53.0 47.5 44.5 19,326 26,430 36,234

Northern Africa10 million or more 1 1 1 11.9 10.1 9.1 10,170 11,001 12,5405 to 10 million — 1 2 — 4.7 8.9 — 5,172 12,2061 to 5 million 6 6 7 17.9 13.3 10.2 15,369 14,446 14,064500,000 to 1 million 8 15 20 6.2 9.1 10.5 5,319 9,961 14,410Fewer than 500,000 … … … 64.0 62.7 61.2 54,798 68,331 84,121

Southern Africa10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million 5 7 7 40.6 49.4 47.3 11,227 16,795 18,337500,000 to 1 million 2 1 2 6.7 1.8 3.1 1,855 615 1,211Fewer than 500,000 … … … 52.7 48.8 49.6 14,575 16,611 19,261

Western Africa10 million or more — 1 1 — 7.7 7.2 — 10,578 14,1625 to 10 million 1 — 1 7.8 0.0 2.8 7,233 — 5,5501 to 5 million 10 16 24 18.9 23.6 25.9 17,384 32,364 50,598500,000 to 1 million 17 26 27 13.3 12.9 9.9 12,213 17,749 19,309Fewer than 500,000 … … … 60.0 55.8 54.1 55,332 76,580 105,725

197Data Tables

TABLE A.4continued


(%) ('000)

2000 2010 2020 2000 2010 2020 2000 2010 2020

AsiaEastern Asia10 million or more 3 4 7 9.9 9.8 12.1 58,839 76,966 113,3545 to 10 million 8 9 10 9.9 8.9 7.5 59,086 70,210 70,8701 to 5 million 64 93 129 21.3 24.3 26.2 126,523 190,704 246,437500,000 to 1 million 112 163 198 12.5 14.5 14.9 74,165 113,597 139,749Fewer than 500,000 … … … 46.4 42.5 39.4 276,063 333,211 370,274

South-Central Asia10 million or more 5 5 5 14.6 15.0 14.2 65,180 85,523 103,8545 to 10 million 5 7 10 6.6 8.2 10.0 29,694 46,607 73,1611 to 5 million 41 57 69 15.2 17.4 16.8 68,047 99,505 123,437500,000 to 1 million 49 68 88 7.8 8.1 8.2 34,884 46,266 60,441Fewer than 500,000 … … … 55.8 51.3 50.8 249,620 293,211 372,146

South-Eastern Asia10 million or more — 1 2 — 4.7 7.8 — 11,628 23,9435 to 10 million 3 3 4 12.5 9.1 8.7 24,680 22,354 26,6441 to 5 million 14 17 21 14.9 13.7 12.0 29,437 33,688 36,772500,000 to 1 million 15 20 28 4.9 5.6 6.0 9,727 13,785 18,235Fewer than 500,000 … … … 67.7 67.0 65.4 133,516 165,246 199,818

Western Asia10 million or more — 1 1 — 6.8 6.2 — 10,525 11,6895 to 10 million 2 1 2 11.5 3.8 6.9 13,944 5,891 13,1311 to 5 million 18 24 30 26.7 31.4 31.6 32,391 48,593 59,883500,000 to 1 million 18 24 31 10.1 10.9 11.3 12,231 16,878 21,353Fewer than 500,000 … … … 51.8 47.1 44.1 62,873 72,927 83,609

EuropeEastern Europe10 million or more 1 1 1 4.8 5.3 5.3 10,005 10,550 10,6625 to 10 million — — — — — — — — —1 to 5 million 23 20 19 16.4 15.4 15.1 34,034 30,975 30,190500,000 to 1 million 29 34 34 8.9 11.2 11.5 18,556 22,459 22,993Fewer than 500,000 … … … 69.8 68.2 68.1 144,814 136,954 136,119

Northern Europe10 million or more — — — — — — — — —5 to 10 million 1 1 1 11.2 11.0 10.5 8,225 8,631 8,7531 to 5 million 7 8 8 14.3 15.3 15.0 10,501 11,958 12,520500,000 to 1 million 9 9 11 9.0 8.1 9.1 6,618 6,315 7,608Fewer than 500,000 … … … 65.5 65.6 65.5 48,159 51,313 54,823

Southern Europe10 million or more — — — — — — — — —5 to 10 million 1 2 2 5.3 10.5 10.6 5,014 10,935 11,8231 to 5 million 9 8 8 24.3 18.1 17.2 23,083 18,823 19,209500,000 to 1 million 18 18 19 12.5 11.6 11.6 11,834 12,090 12,998Fewer than 500,000 … … … 58.0 59.8 60.6 55,083 62,361 67,634

Western Europe10 million or more — 1 1 — 7.0 6.9 — 10,485 10,8805 to 10 million 1 — — 7.0 0.0 0.0 9,739 — —1 to 5 million 10 12 13 11.1 12.3 12.8 15,434 18,374 20,072500,000 to 1 million 19 20 20 9.2 8.5 8.1 12,710 12,780 12,729Fewer than 500,000 … … … 72.6 72.2 72.2 100,612 108,291 113,474

Latin America and the CaribbeanCaribbean10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million 4 4 4 33.5 32.5 31.6 7,930 9,196 10,278500,000 to 1 million 1 3 3 2.4 6.3 6.0 580 1,772 1,946Fewer than 500,000 … … … 64.1 61.2 62.4 15,197 17,310 20,286

Central America10 million or more 1 1 1 19.4 17.7 16.1 18,022 19,460 20,4765 to 10 million — — — — — — — — —1 to 5 million 11 16 19 19.9 25.1 27.0 18,461 27,655 34,476500,000 to 1 million 22 24 25 16.4 15.4 14.4 15,262 17,016 18,349Fewer than 500,000 … … … 44.3 41.8 42.5 41,204 46,120 54,162

South America10 million or more 3 3 5 14.4 13.7 18.3 39,749 45,287 68,1245 to 10 million 3 4 2 6.8 8.9 3.4 18,925 29,244 12,8281 to 5 million 28 35 36 20.6 22.7 23.1 57,124 74,976 86,069500,000 to 1 million 31 30 34 7.7 6.5 6.9 21,421 21,328 25,635Fewer than 500,000 … … … 50.4 48.3 48.4 139,545 159,394 180,519

Northern America10 million or more 2 2 2 11.8 11.1 10.4 29,659 32,187 33,8375 to 10 million 2 4 6 5.4 9.0 11.8 13,494 26,029 38,1161 to 5 million 37 42 44 33.8 32.9 29.8 85,310 95,001 96,533500,000 to 1 million 39 40 43 10.9 9.8 9.4 27,380 28,282 30,579Fewer than 500,000 … … … 38.2 37.2 38.6 96,311 107,304 125,214


TABLE A.4continued


(%) ('000)

2000 2010 2020 2000 2010 2020 2000 2010 2020

Oceania10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million 6 6 6 57.7 57.3 55.3 12,652 14,423 15,711500,000 to 1 million — 2 2 — 4.3 4.3 — 1,082 1,210Fewer than 500,000 … … … 42.3 38.4 40.4 9,280 9,663 11,484

Australia/New Zealand10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million 6 6 6 63.2 63.0 61.6 12,652 14,423 15,711500,000 to 1 million — 2 2 — 4.7 4.7 — 1,082 1,210Fewer than 500,000 … … … 36.8 32.2 33.7 7,372 7,374 8,595

Melanesia10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million — — — — — — — — —500,000 to 1 million — — — — — — — — —Fewer than 500,000 … … … 100.0 100.0 100.0 1,329 1,614 2,110

Micronesia10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million — — — — — — — — —500,000 to 1 million — — — — — — — — —Fewer than 500,000 … … … 100.0 100.0 100.0 326 390 454

Polynesia10 million or more — — — — — — — — —5 to 10 million — — — — — — — — —1 to 5 million — — — — — — — — —500,000 to 1 million — — — — — — — — —Fewer than 500,000 … … … 100.0 100.0 100.0 253 285 325

Source: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York. The figures in regional aggregates are not consistent withcity data in table C.1.


199Data Tables

COUNTRY LEVEL DATATABLE B.1 Total Population Size, Rate of Change and Population Density


2000 2010 2020 2030 2000–2010 2010–2020 2020–2030 2000 2030

AFRICAAlgeria 30,506 35,423 40,630 44,726 1.49 1.37 0.96 13 19Angola 14,280 18,993 24,507 30,416 2.85 2.55 2.16 11 24Benin 6,659 9,212 12,177 15,399 3.25 2.79 2.35 59 137Botswana 1,723 1,978 2,227 2,434 1.38 1.19 0.89 3 4Burkina Faso 11,676 16,287 21,871 27,940 3.33 2.95 2.45 43 102Burundi 6,473 8,519 10,318 11,936 2.75 1.92 1.46 233 429Cameroon 15,865 19,958 24,349 28,602 2.30 1.99 1.61 33 60Cape Verde 439 513 584 645 1.56 1.30 0.99 109 160Central African Republic 3,746 4,506 5,340 6,150 1.85 1.70 1.41 6 10Chad 8,402 11,506 14,897 19,018 3.14 2.58 2.44 7 15Comoros 552 691 838 975 2.25 1.93 1.51 297 524Congo 3,036 3,759 4,699 5,479 2.14 2.23 1.54 9 16Côte d'Ivoire 17,281 21,571 26,954 32,551 2.22 2.23 1.89 54 101Democratic Republic of the Congo 50,829 67,827 87,640 108,594 2.88 2.56 2.14 22 46Djibouti 730 879 1,027 1,192 1.86 1.56 1.49 31 51Egypt 70,174 84,474 98,638 110,907 1.85 1.55 1.17 70 111Equatorial Guinea 529 693 875 1,067 2.70 2.33 1.98 19 38Eritrea 3,657 5,224 6,719 8,086 3.57 2.52 1.85 31 69Ethiopia 65,515 84,976 107,964 131,561 2.60 2.39 1.98 59 119Gabon 1,233 1,501 1,779 2,044 1.97 1.70 1.39 5 8Gambia 1,302 1,751 2,227 2,736 2.96 2.40 2.06 115 242Ghana 19,529 24,333 29,567 34,884 2.20 1.95 1.65 82 146Guinea 8,384 10,324 13,467 16,897 2.08 2.66 2.27 34 69Guinea-Bissau 1,304 1,647 2,065 2,536 2.34 2.26 2.05 36 70Kenya 31,441 40,863 52,034 63,199 2.62 2.42 1.94 54 109Lesotho 1,889 2,084 2,244 2,359 0.98 0.74 0.50 62 78Liberia 2,824 4,102 5,253 6,470 3.73 2.47 2.08 25 58Libyan Arab Jamahiriya 5,346 6,546 7,699 8,519 2.03 1.62 1.01 3 5Madagascar 15,275 20,146 25,687 31,528 2.77 2.43 2.05 26 54Malawi 11,831 15,692 20,537 25,897 2.82 2.69 2.32 100 219Mali 10,523 13,323 16,767 20,467 2.36 2.30 1.99 8 17Mauritania 2,604 3,366 4,091 4,791 2.57 1.95 1.58 3 5Mauritius1 1,195 1,297 1,372 1,420 0.82 0.56 0.34 586 696Mayotte 149 199 250 302 2.89 2.28 1.89 397 808Morocco 28,827 32,381 36,200 39,259 1.16 1.11 0.81 65 88Mozambique 18,249 23,406 28,545 33,894 2.49 1.98 1.72 23 42Namibia 1,824 2,212 2,614 2,993 1.93 1.67 1.35 2 4Niger 11,031 15,891 22,947 32,563 3.65 3.67 3.50 9 26Nigeria 124,842 158,259 193,252 226,651 2.37 2.00 1.59 135 245Réunion 724 837 931 1,009 1.45 1.06 0.80 288 402Rwanda 7,958 10,277 13,233 16,104 2.56 2.53 1.96 302 611Saint Helena2 5 4 4 5 -2.23 0.00 2.23 42 38São Tomé and Príncipe 140 165 197 234 1.64 1.77 1.72 145 242Senegal 9,902 12,861 16,197 19,541 2.61 2.31 1.88 50 99Seychelles 81 85 89 93 0.48 0.46 0.44 178 205Sierra Leone 4,228 5,836 7,318 8,943 3.22 2.26 2.01 59 125Somalia 7,394 9,359 12,246 15,744 2.36 2.69 2.51 12 25South Africa 44,872 50,492 52,671 54,726 1.18 0.42 0.38 37 45Sudan 34,904 43,192 52,309 60,995 2.13 1.92 1.54 14 24Swaziland 1,080 1,202 1,376 1,524 1.07 1.35 1.02 62 88Togo 5,247 6,780 8,445 10,115 2.56 2.20 1.80 92 178Tunisia 9,452 10,374 11,366 12,127 0.93 0.91 0.65 58 74Uganda 24,433 33,796 46,319 60,819 3.24 3.15 2.72 101 252United Republic of Tanzania 34,131 45,040 59,603 75,498 2.77 2.80 2.36 36 80Western Sahara 315 530 723 819 5.20 3.11 1.25 1 3Zambia 10,467 13,257 16,916 20,889 2.36 2.44 2.11 14 28Zimbabwe 12,455 12,644 15,571 17,917 0.15 2.08 1.40 32 46ASIAAfghanistan 20,536 29,117 39,585 50,649 3.49 3.07 2.46 31 78Armenia 3,076 3,090 3,175 3,170 0.05 0.27 -0.02 103 106Azerbaijan 8,121 8,934 9,838 10,323 0.95 0.96 0.48 94 119Bahrain 650 807 953 1,085 2.16 1.66 1.30 937 1,564Bangladesh 140,767 164,425 185,552 203,214 1.55 1.21 0.91 978 1,411Bhutan 561 708 820 902 2.33 1.47 0.95 12 19Brunei Darussalam 333 407 478 547 2.01 1.61 1.35 58 95Cambodia 12,760 15,053 17,707 20,100 1.65 1.62 1.27 70 111China3 1,266,954 1,354,146 1,431,155 1,462,468 0.67 0.55 0.22 132 152China, Hong Kong SAR4 6,667 7,069 7,701 8,185 0.59 0.86 0.61 6,066 7,448China, Macao SAR5 441 548 588 611 2.17 0.70 0.38 16,958 23,507Cyprus 787 880 970 1,053 1.12 0.97 0.82 85 114Democratic People's Republic of Korea 22,859 23,991 24,802 25,301 0.48 0.33 0.20 190 210Georgia 4,745 4,219 3,982 3,779 -1.17 -0.58 -0.52 68 54India 1,042,590 1,214,464 1,367,225 1,484,598 1.53 1.18 0.82 317 452Indonesia 205,280 232,517 254,218 271,485 1.25 0.89 0.66 108 143Iran (Islamic Republic of) 66,903 75,078 83,740 89,936 1.15 1.09 0.71 41 55Iraq 24,652 31,467 40,228 48,909 2.44 2.46 1.95 56 112


TABLE B.1continued


2000 2010 2020 2030 2000–2010 2010–2020 2020–2030 2000 2030

Israel 6,084 7,285 8,307 9,219 1.80 1.31 1.04 275 416Japan 126,706 126,995 123,664 117,424 0.02 -0.27 -0.52 335 311Jordan 4,853 6,472 7,519 8,616 2.88 1.50 1.36 54 96Kazakhstan 14,957 15,753 16,726 17,244 0.52 0.60 0.30 5 6Kuwait 2,228 3,051 3,690 4,273 3.14 1.90 1.47 125 240Kyrgyzstan 4,955 5,550 6,159 6,543 1.13 1.04 0.60 25 33Lao People's Democratic Republic 5,403 6,436 7,651 8,854 1.75 1.73 1.46 23 37Lebanon 3,772 4,255 4,587 4,858 1.20 0.75 0.57 363 467Malaysia 23,274 27,914 32,017 35,275 1.82 1.37 0.97 71 107Maldives 272 314 362 403 1.44 1.42 1.07 914 1,352Mongolia 2,389 2,701 3,002 3,236 1.23 1.06 0.75 2 2Myanmar 46,610 50,496 55,497 59,353 0.80 0.94 0.67 69 88Nepal 24,432 29,853 35,269 40,646 2.00 1.67 1.42 166 276Occupied Palestinian Territory 3,149 4,409 5,806 7,320 3.37 2.75 2.32 523 1,216Oman 2,402 2,905 3,495 4,048 1.90 1.85 1.47 8 13Pakistan 148,132 184,753 226,187 265,690 2.21 2.02 1.61 186 334Philippines 77,689 93,617 109,683 124,384 1.86 1.58 1.26 259 415Qatar 617 1,508 1,740 1,951 8.94 1.43 1.14 56 177Republic of Korea 46,429 48,501 49,475 49,146 0.44 0.20 -0.07 466 494Saudi Arabia 20,808 26,246 31,608 36,545 2.32 1.86 1.45 10 17Singapore 4,018 4,837 5,219 5,460 1.86 0.76 0.45 5,883 7,994Sri Lanka 18,767 20,410 21,713 22,194 0.84 0.62 0.22 286 338Syrian Arab Republic 16,511 22,505 26,475 30,560 3.10 1.62 1.43 89 165Tajikistan 6,173 7,075 8,446 9,618 1.36 1.77 1.30 43 67Thailand 62,347 68,139 71,443 73,462 0.89 0.47 0.28 122 143Timor-Leste 815 1,171 1,618 2,125 3.62 3.23 2.73 55 143Turkey 66,460 75,705 83,873 90,375 1.30 1.02 0.75 85 115Turkmenistan 4,502 5,177 5,816 6,276 1.40 1.16 0.76 9 13United Arab Emirates 3,238 4,707 5,660 6,555 3.74 1.84 1.47 39 78Uzbekistan 24,776 27,794 31,185 33,933 1.15 1.15 0.84 55 76Viet Nam 78,663 89,029 98,011 105,447 1.24 0.96 0.73 237 318Yemen 18,182 24,256 31,635 39,350 2.88 2.66 2.18 34 75EUROPEAlbania 3,068 3,169 3,338 3,416 0.32 0.52 0.23 107 119Andorra 66 87 100 113 2.76 1.39 1.22 142 242Austria 8,005 8,387 8,539 8,637 0.47 0.18 0.11 95 103Belarus 10,054 9,588 9,112 8,564 -0.47 -0.51 -0.62 48 41Belgium 10,193 10,698 11,048 11,303 0.48 0.32 0.23 334 370Bosnia and Herzegovina 3,694 3,760 3,677 3,520 0.18 -0.22 -0.44 72 69Bulgaria 8,006 7,497 7,017 6,469 -0.66 -0.66 -0.81 72 58Channel Islands6 147 150 151 151 0.20 0.07 0.00 752 776Croatia 4,505 4,410 4,318 4,180 -0.21 -0.21 -0.32 80 74Czech Republic 10,224 10,411 10,568 10,520 0.18 0.15 -0.05 130 133Denmark 5,335 5,481 5,557 5,616 0.27 0.14 0.11 124 130Estonia 1,370 1,339 1,333 1,301 -0.23 -0.04 -0.24 30 29Faeroe Islands 46 50 53 56 0.83 0.58 0.55 33 40Finland7 5,173 5,346 5,496 5,544 0.33 0.28 0.09 15 16France 59,128 62,637 64,931 66,474 0.58 0.36 0.23 107 121Germany 82,075 82,057 80,422 77,854 0.00 -0.20 -0.32 230 218Gibraltar 29 31 32 31 0.67 0.32 -0.32 4,818 5,240Greece 10,942 11,183 11,284 11,234 0.22 0.09 -0.04 83 85Holy See8 1 1 1 1 0.00 0.00 0.00 1,789 1,739Hungary 10,215 9,973 9,766 9,509 -0.24 -0.21 -0.27 110 102Iceland 281 329 370 392 1.58 1.17 0.58 3 4Ireland 3,804 4,589 5,145 5,573 1.88 1.14 0.80 54 79Isle of Man 77 80 81 80 0.38 0.12 -0.12 134 140Italy 57,116 60,098 60,408 59,549 0.51 0.05 -0.14 190 198Latvia 2,374 2,240 2,153 2,049 -0.58 -0.40 -0.50 37 32Liechtenstein 33 36 39 42 0.87 0.80 0.74 205 259Lithuania 3,501 3,255 3,058 2,909 -0.73 -0.62 -0.50 54 45Luxembourg 437 492 550 615 1.19 1.11 1.12 169 238Malta 389 410 422 427 0.53 0.29 0.12 1,231 1,351Moldova 4,100 3,576 3,378 3,182 -1.37 -0.57 -0.60 121 94Monaco 32 33 34 35 0.31 0.30 0.29 21,478 23,738Montenegro 661 626 631 634 -0.54 0.08 0.05 48 46Netherlands 15,915 16,653 17,143 17,498 0.45 0.29 0.20 383 421Norway9 4,484 4,855 5,200 5,518 0.79 0.69 0.59 12 14Poland 38,433 38,038 37,497 36,187 -0.10 -0.14 -0.36 119 112Portugal 10,226 10,732 10,767 10,620 0.48 0.03 -0.14 111 115Romania 22,138 21,190 20,380 19,489 -0.44 -0.39 -0.45 93 82Russian Federation 146,670 140,367 135,406 128,864 -0.44 -0.36 -0.50 9 8San Marino 27 32 33 33 1.70 0.31 0.00 442 548Serbia 10,134 9,856 9,783 9,644 -0.28 -0.07 -0.14 115 109Slovakia 5,379 5,412 5,442 5,348 0.06 0.06 -0.17 110 109Slovenia 1,985 2,025 2,053 2,037 0.20 0.14 -0.08 98 101Spain 40,264 45,317 48,564 49,772 1.18 0.69 0.25 80 98Sweden 8,860 9,293 9,713 10,076 0.48 0.44 0.37 20 22Switzerland 7,184 7,595 7,879 8,148 0.56 0.37 0.34 174 197TFYR Macedonia10 2,012 2,043 2,046 2,016 0.15 0.01 -0.15 78 78

201Data Tables

TABLE B.1continued


2000 2010 2020 2030 2000–2010 2010–2020 2020–2030 2000 2030

Ukraine 48,870 45,433 42,945 40,188 -0.73 -0.56 -0.66 81 67United Kingdom 58,907 61,899 65,090 67,956 0.50 0.50 0.43 243 280

LATIN AMERICA AND THE CARIBBEANAnguilla 11 15 18 19 3.10 1.82 0.54 123 207Antigua and Barbuda 77 89 97 105 1.45 0.86 0.79 175 237Argentina 36,939 40,666 44,304 47,255 0.96 0.86 0.64 13 17Aruba 91 107 111 112 1.62 0.37 0.09 504 625Bahamas 305 346 384 418 1.26 1.04 0.85 22 30Barbados 252 257 262 260 0.20 0.19 -0.08 585 606Belize 252 313 375 430 2.17 1.81 1.37 11 19Bolivia 8,317 10,031 11,638 13,034 1.87 1.49 1.13 8 12Brazil 174,174 195,423 209,051 217,146 1.15 0.67 0.38 20 26British Virgin Islands 21 23 25 27 0.91 0.83 0.77 136 178Cayman Islands 40 57 61 65 3.54 0.68 0.64 153 246Chile 15,419 17,135 18,639 19,779 1.06 0.84 0.59 20 26Colombia 39,773 46,300 52,278 57,264 1.52 1.21 0.91 35 50Costa Rica 3,931 4,640 5,250 5,762 1.66 1.24 0.93 77 113Cuba 11,087 11,204 11,193 11,019 0.10 -0.01 -0.16 100 99Dominica 68 67 67 69 -0.15 0.00 0.29 91 91Dominican Republic 8,830 10,225 11,451 12,431 1.47 1.13 0.82 182 256Ecuador 12,310 13,775 15,376 16,679 1.12 1.10 0.81 43 59El Salvador 5,945 6,194 6,618 7,177 0.41 0.66 0.81 283 341Falkland Islands (Malvinas) 3 3 3 3 0.00 0.00 0.00 0 0French Guiana 165 231 292 354 3.36 2.34 1.93 2 4Grenada 101 104 108 108 0.29 0.38 0.00 294 315Guadeloupe 429 467 484 492 0.85 0.36 0.16 252 288Guatemala 11,231 14,377 18,091 21,692 2.47 2.30 1.82 103 199Guyana 756 761 745 714 0.07 -0.21 -0.43 4 3Haiti 8,648 10,188 11,722 13,196 1.64 1.40 1.18 312 476Honduras 6,230 7,616 9,136 10,492 2.01 1.82 1.38 56 94Jamaica 2,568 2,730 2,834 2,873 0.61 0.37 0.14 234 261Martinique 385 406 415 418 0.53 0.22 0.07 349 379Mexico 99,531 110,645 119,682 126,457 1.06 0.79 0.55 51 65Montserrat 5 6 6 7 1.82 0.00 1.54 49 66Netherlands Antilles 181 201 210 209 1.05 0.44 -0.05 226 262Nicaragua 5,101 5,822 6,682 7,387 1.32 1.38 1.00 39 57Panama 2,951 3,508 4,027 4,488 1.73 1.38 1.08 39 59Paraguay 5,350 6,460 7,533 8,483 1.89 1.54 1.19 13 21Peru 26,004 29,496 32,881 36,006 1.26 1.09 0.91 20 28Puerto Rico 3,819 3,998 4,135 4,195 0.46 0.34 0.14 430 473Saint Kitts and Nevis 46 52 59 64 1.23 1.26 0.81 176 244Saint Lucia 157 174 190 204 1.03 0.88 0.71 292 378Saint Vincent and the Grenadines 108 109 110 113 0.09 0.09 0.27 278 290Suriname 467 524 568 602 1.15 0.81 0.58 3 4Trinidad and Tobago 1,295 1,344 1,384 1,382 0.37 0.29 -0.01 252 269Turks and Caicos Islands 19 33 36 39 5.52 0.87 0.80 44 90United States Virgin Islands 109 109 106 99 0.00 -0.28 -0.68 313 284Uruguay 3,321 3,372 3,493 3,588 0.15 0.35 0.27 19 21Venezuela (Bolivarian Republic of) 24,408 29,044 33,412 37,145 1.74 1.40 1.06 27 41NORTHERN AMERICABermuda 63 65 66 66 0.31 0.15 0.00 1,186 1,243Canada 30,687 33,890 37,101 40,096 0.99 0.91 0.78 3 4Greenland 56 57 57 55 0.18 0.00 -0.36 0 0Saint-Pierre-et-Miquelon 6 6 6 6 0.00 0.00 0.00 26 25United States of America 287,842 317,641 346,153 369,981 0.99 0.86 0.67 30 38OCEANIAAmerican Samoa 58 69 80 91 1.74 1.48 1.29 290 460Australia11 19,171 21,512 23,675 25,656 1.15 0.96 0.80 2 3Cook Islands 18 20 21 22 1.05 0.49 0.47 74 93Fiji 802 854 888 918 0.63 0.39 0.33 44 50French Polynesia 236 272 304 329 1.42 1.11 0.79 59 82Guam 155 180 201 220 1.50 1.10 0.90 283 401Kiribati 84 100 115 131 1.74 1.40 1.30 116 180Marshall Islands 52 63 75 83 1.92 1.74 1.01 288 457Micronesia (Federated States of) 107 111 118 125 0.37 0.61 0.58 153 178Nauru 10 10 11 11 0.00 0.95 0.00 478 527New Caledonia 215 254 288 318 1.67 1.26 0.99 12 17New Zealand 3,868 4,303 4,669 4,972 1.07 0.82 0.63 14 18Niue 2 1 1 1 -6.93 0.00 0.00 7 4Northern Mariana Islands 69 88 104 119 2.43 1.67 1.35 149 256Palau 19 21 22 25 1.00 0.47 1.28 42 53Papua New Guinea 5,388 6,888 8,468 10,058 2.46 2.07 1.72 12 22Pitcairn 0 0 0 0 0.00 0.00 0.00 12 11Samoa 177 179 184 191 0.11 0.28 0.37 62 68Solomon Islands 416 536 662 788 2.53 2.11 1.74 14 27Tokelau 2 1 1 1 -6.93 0.00 0.00 128 101Tonga 99 104 108 115 0.49 0.38 0.63 152 178


TABLE B.1continued


2000 2010 2020 2030 2000–2010 2010–2020 2020–2030 2000 2030

Tuvalu 10 10 10 11 0.00 0.00 0.95 367 419Vanuatu 190 246 307 369 2.58 2.22 1.84 16 30Wallis and Futuna Islands 15 15 17 17 0.00 1.25 0.00 73 85Sources: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York; United Nations Department of Economic and SocialAffairs, Population Division (2009) World Population Prospects: The 2008 Revision, United Nations, New York.

Notes:(1) Including Agalega, Rodrigues, and Saint Brandon.(2) Including Ascension, and Tristan da Cunha.(3) For statistical purposes, the data for China do not include Hong Kong and Macao, Special Administrative Regions (SAR) of China.(4) As of 1 July 1997, Hong Kong became a Special Administrative Region (SAR) of China.(5) As of 20 December 1999, Macao became a Special Administrative Region (SAR) of China.(6) Refers to Guernsey and Jersey.(7) Including Åland Islands.(8) Refers to the Vatican City State.(9) Including Svalbard and Jan Mayen Islands.(10) The former Yugoslav Republic of Macedonia.(11) Including Christmas Island, Cocos (Keeling) Islands, and Norfolk Island.

203Data Tables

TABLE B.2Urban and Rural Population Size and Rate of Change



2000 2010 2020 2030 2000– 2010– 2020– 2000 2010 2020 2030 2000– 2010– 2020–2010 2020 2030 2010 2020 2030

AFRICAAlgeria 18,246 23,555 29,194 34,097 2.55 2.15 1.55 12,260 11,868 11,436 10,630 -0.32 -0.37 -0.73Angola 6,995 11,112 16,184 21,784 4.63 3.76 2.97 7,284 7,881 8,323 8,631 0.79 0.55 0.36Benin 2,553 3,873 5,751 8,275 4.17 3.95 3.64 4,107 5,339 6,426 7,124 2.62 1.85 1.03Botswana 917 1,209 1,506 1,769 2.76 2.20 1.61 806 769 722 665 -0.47 -0.63 -0.82Burkina Faso 2,083 4,184 7,523 11,958 6.97 5.87 4.63 9,593 12,103 14,348 15,982 2.32 1.70 1.08Burundi 536 937 1,524 2,362 5.59 4.86 4.38 5,937 7,582 8,794 9,574 2.45 1.48 0.85Cameroon 7,910 11,655 15,941 20,304 3.88 3.13 2.42 7,955 8,303 8,408 8,298 0.43 0.13 -0.13Cape Verde 235 313 394 468 2.87 2.30 1.72 204 199 190 177 -0.25 -0.46 -0.71Central African Republic 1,410 1,755 2,268 2,978 2.19 2.56 2.72 2,336 2,751 3,072 3,171 1.64 1.10 0.32Chad 1,964 3,179 5,054 7,843 4.82 4.64 4.39 6,438 8,328 9,843 11,174 2.57 1.67 1.27Comoros 155 195 259 356 2.30 2.84 3.18 397 496 580 619 2.23 1.56 0.65Congo 1,770 2,335 3,118 3,883 2.77 2.89 2.19 1,265 1,424 1,582 1,596 1.18 1.05 0.09Côte d'Ivoire 7,524 10,906 15,574 20,873 3.71 3.56 2.93 9,757 10,664 11,380 11,678 0.89 0.65 0.26Democratic Republic of the Congo 15,168 23,887 36,834 53,382 4.54 4.33 3.71 35,662 43,940 50,806 55,212 2.09 1.45 0.83Djibouti 555 670 798 956 1.88 1.75 1.81 175 209 230 237 1.78 0.96 0.30Egypt 30,032 36,664 45,301 56,477 2.00 2.12 2.21 40,142 47,810 53,336 54,430 1.75 1.09 0.20Equatorial Guinea 205 275 379 527 2.94 3.21 3.30 324 418 496 540 2.55 1.71 0.85Eritrea 650 1,127 1,845 2,780 5.50 4.93 4.10 3,007 4,097 4,874 5,305 3.09 1.74 0.85Ethiopia 9,762 14,158 20,800 31,383 3.72 3.85 4.11 55,753 70,818 87,165 100,178 2.39 2.08 1.39Gabon 989 1,292 1,579 1,853 2.67 2.01 1.60 245 210 200 192 -1.54 -0.49 -0.41Gambia 639 1,018 1,449 1,943 4.66 3.53 2.93 663 733 779 793 1.00 0.61 0.18Ghana 8,584 12,524 17,274 22,565 3.78 3.22 2.67 10,945 11,808 12,293 12,319 0.76 0.40 0.02Guinea 2,603 3,651 5,580 8,219 3.38 4.24 3.87 5,781 6,673 7,887 8,678 1.43 1.67 0.96Guinea-Bissau 387 494 678 979 2.44 3.17 3.67 917 1,153 1,387 1,557 2.29 1.85 1.16Kenya 6,204 9,064 13,826 20,884 3.79 4.22 4.12 25,237 31,799 38,208 42,315 2.31 1.84 1.02Lesotho 377 560 775 999 3.96 3.25 2.54 1,511 1,524 1,469 1,360 0.09 -0.37 -0.77Liberia 1,252 1,961 2,739 3,725 4.49 3.34 3.07 1,572 2,141 2,514 2,745 3.09 1.61 0.88Libyan Arab Jamahiriya 4,083 5,098 6,181 7,060 2.22 1.93 1.33 1,263 1,447 1,517 1,459 1.36 0.47 -0.39Madagascar 4,143 6,082 8,953 13,048 3.84 3.87 3.77 11,132 14,064 16,734 18,480 2.34 1.74 0.99Malawi 1,796 3,102 5,240 8,395 5.46 5.24 4.71 10,036 12,590 15,297 17,502 2.27 1.95 1.35Mali 2,982 4,777 7,325 10,491 4.71 4.27 3.59 7,541 8,546 9,442 9,976 1.25 1.00 0.55Mauritania 1,041 1,395 1,859 2,478 2.93 2.87 2.87 1,563 1,971 2,232 2,313 2.32 1.24 0.36Mauritius1 510 542 595 681 0.61 0.93 1.35 685 754 777 738 0.96 0.30 -0.51Mayotte 71 100 129 168 3.42 2.55 2.64 78 99 121 134 2.38 2.01 1.02Morocco 15,375 18,859 23,158 27,157 2.04 2.05 1.59 13,452 13,523 13,042 12,102 0.05 -0.36 -0.75Mozambique 5,601 8,996 13,208 18,199 4.74 3.84 3.21 12,649 14,410 15,338 15,695 1.30 0.62 0.23Namibia 590 840 1,161 1,541 3.53 3.24 2.83 1,234 1,372 1,453 1,452 1.06 0.57 -0.01Niger 1,785 2,719 4,417 7,641 4.21 4.85 5.48 9,246 13,173 18,529 24,922 3.54 3.41 2.96Nigeria 53,078 78,818 109,859 144,116 3.95 3.32 2.71 71,765 79,441 83,394 82,534 1.02 0.49 -0.10Réunion 650 787 891 972 1.91 1.24 0.87 73 50 40 37 -3.78 -2.23 -0.78Rwanda 1,096 1,938 2,993 4,550 5.70 4.35 4.19 6,862 8,340 10,241 11,554 1.95 2.05 1.21Saint Helena2 2 2 2 2 0.00 0.00 0.00 3 3 3 2 0.00 0.00 -4.05São Tomé and Príncipe 75 103 136 173 3.17 2.78 2.41 65 62 61 61 -0.47 -0.16 0.00Senegal 3,995 5,450 7,524 10,269 3.11 3.22 3.11 5,907 7,410 8,673 9,273 2.27 1.57 0.67Seychelles 41 47 54 62 1.37 1.39 1.38 40 38 35 31 -0.51 -0.82 -1.21Sierra Leone 1,501 2,241 3,134 4,384 4.01 3.35 3.36 2,727 3,595 4,184 4,559 2.76 1.52 0.86Somalia 2,458 3,505 5,268 7,851 3.55 4.07 3.99 4,936 5,854 6,978 7,893 1.71 1.76 1.23South Africa 25,528 31,155 35,060 39,032 1.99 1.18 1.07 19,344 19,338 17,611 15,694 0.00 -0.94 -1.15Sudan 11,661 17,322 24,804 33,267 3.96 3.59 2.94 23,243 25,871 27,505 27,728 1.07 0.61 0.08Swaziland 244 257 307 400 0.52 1.78 2.65 835 945 1,069 1,125 1.24 1.23 0.51Togo 1,917 2,945 4,261 5,795 4.29 3.69 3.07 3,331 3,835 4,183 4,319 1.41 0.87 0.32Tunisia 5,996 6,980 8,096 9,115 1.52 1.48 1.19 3,456 3,394 3,270 3,012 -0.18 -0.37 -0.82Uganda 2,952 4,493 7,381 12,503 4.20 4.96 5.27 21,481 29,303 38,939 48,315 3.11 2.84 2.16United Republic of Tanzania 7,614 11,883 18,945 29,190 4.45 4.66 4.32 26,517 33,157 40,658 46,308 2.23 2.04 1.30Western Sahara 264 434 606 704 4.97 3.34 1.50 51 96 116 115 6.33 1.89 -0.09Zambia 3,643 4,733 6,584 9,340 2.62 3.30 3.50 6,824 8,524 10,332 11,549 2.22 1.92 1.11Zimbabwe 4,205 4,837 6,839 9,086 1.40 3.46 2.84 8,251 7,807 8,732 8,832 -0.55 1.12 0.11ASIAAfghanistan 4,148 6,581 10,450 16,296 4.62 4.62 4.44 16,388 22,537 29,134 34,353 3.19 2.57 1.65Armenia 1,989 1,984 2,087 2,186 -0.03 0.51 0.46 1,087 1,107 1,088 983 0.18 -0.17 -1.01Azerbaijan 4,158 4,639 5,332 6,044 1.09 1.39 1.25 3,964 4,294 4,506 4,279 0.80 0.48 -0.52Bahrain 574 715 852 984 2.20 1.75 1.44 76 92 101 102 1.91 0.93 0.10Bangladesh 33,208 46,149 62,886 83,408 3.29 3.09 2.82 107,559 118,276 122,667 119,807 0.95 0.36 -0.24Bhutan 143 246 348 451 5.42 3.47 2.59 419 463 472 451 1.00 0.19 -0.46Brunei Darussalam 237 308 379 450 2.62 2.07 1.72 96 99 99 97 0.31 0.00 -0.20Cambodia 2,157 3,027 4,214 5,870 3.39 3.31 3.31 10,603 12,026 13,493 14,230 1.26 1.15 0.53China3 453,029 635,839 786,761 905,449 3.39 2.13 1.41 813,925 718,307 644,394 557,019 -1.25 -1.09 -1.46China, Hong Kong SAR4 6,667 7,069 7,701 8,185 0.59 0.86 0.61 — — — — — — —China, Macao SAR5 441 548 588 611 2.17 0.70 0.38 — — — — — — —Cyprus 540 619 705 797 1.37 1.30 1.23 247 261 265 256 0.55 0.15 -0.35Democratic People's Republic of Korea 13,581 14,446 15,413 16,633 0.62 0.65 0.76 9,278 9,545 9,389 8,668 0.28 -0.16 -0.80Georgia 2,498 2,225 2,177 2,218 -1.16 -0.22 0.19 2,247 1,994 1,806 1,561 -1.19 -0.99 -1.46India 288,430 364,459 463,328 590,091 2.34 2.40 2.42 754,160 850,005 903,896 894,507 1.20 0.61 -0.10Indonesia 86,219 102,960 122,257 145,776 1.77 1.72 1.76 119,061 129,557 131,961 125,709 0.84 0.18 -0.49Iran (Islamic Republic of) 42,952 53,120 63,596 71,767 2.12 1.80 1.21 23,951 21,958 20,145 18,169 -0.87 -0.86 -1.03


TABLE B.2continued



2000 2010 2020 2030 2000– 2010– 2020– 2000 2010 2020 2030 2000– 2010– 2020–2010 2020 2030 2010 2020 2030

Iraq 16,722 20,822 26,772 33,930 2.19 2.51 2.37 7,931 10,644 13,455 14,979 2.94 2.34 1.07Israel 5,563 6,692 7,673 8,583 1.85 1.37 1.12 521 594 634 636 1.31 0.65 0.03Japan 82,633 84,875 85,848 85,700 0.27 0.11 -0.02 44,073 42,120 37,817 31,724 -0.45 -1.08 -1.76Jordan 3,798 5,083 5,998 7,063 2.91 1.66 1.63 1,055 1,390 1,520 1,554 2.76 0.89 0.22Kazakhstan 8,417 9,217 10,417 11,525 0.91 1.22 1.01 6,539 6,537 6,309 5,718 0.00 -0.36 -0.98Kuwait 2,188 3,001 3,637 4,218 3.16 1.92 1.48 40 49 53 55 2.03 0.78 0.37Kyrgyzstan 1,744 1,918 2,202 2,625 0.95 1.38 1.76 3,211 3,633 3,957 3,918 1.23 0.85 -0.10Lao People's Democratic Republic 1,187 2,136 3,381 4,699 5.88 4.59 3.29 4,216 4,300 4,269 4,155 0.20 -0.07 -0.27Lebanon 3,244 3,712 4,065 4,374 1.35 0.91 0.73 528 543 522 484 0.28 -0.39 -0.76Malaysia 14,424 20,146 25,128 28,999 3.34 2.21 1.43 8,849 7,768 6,889 6,277 -1.30 -1.20 -0.93Maldives 75 126 186 242 5.19 3.89 2.63 197 188 175 161 -0.47 -0.72 -0.83Mongolia 1,358 1,675 2,010 2,316 2.10 1.82 1.42 1,031 1,026 992 920 -0.05 -0.34 -0.75Myanmar 12,956 16,990 22,570 28,545 2.71 2.84 2.35 33,654 33,505 32,927 30,808 -0.04 -0.17 -0.67Nepal 3,281 5,559 8,739 12,902 5.27 4.52 3.90 21,150 24,294 26,529 27,744 1.39 0.88 0.45Occupied Palestinian Territory 2,267 3,269 4,447 5,810 3.66 3.08 2.67 883 1,140 1,359 1,510 2.55 1.76 1.05Oman 1,719 2,122 2,645 3,184 2.11 2.20 1.85 683 783 850 864 1.37 0.82 0.16Pakistan 49,088 66,318 90,199 121,218 3.01 3.08 2.96 99,045 118,435 135,987 144,472 1.79 1.38 0.61Philippines 37,283 45,781 57,657 72,555 2.05 2.31 2.30 40,406 47,836 52,026 51,829 1.69 0.84 -0.04Qatar 586 1,445 1,679 1,891 9.03 1.50 1.19 31 63 62 60 7.09 -0.16 -0.33Republic of Korea 36,967 40,235 42,362 43,086 0.85 0.52 0.17 9,462 8,265 7,113 6,060 -1.35 -1.50 -1.60Saudi Arabia 16,615 21,541 26,617 31,516 2.60 2.12 1.69 4,193 4,705 4,991 5,030 1.15 0.59 0.08Singapore 4,018 4,837 5,219 5,460 1.86 0.76 0.45 — — — — — — —Sri Lanka 2,971 2,921 3,360 4,339 -0.17 1.40 2.56 15,796 17,489 18,353 17,855 1.02 0.48 -0.28Syrian Arab Republic 8,577 12,545 15,948 19,976 3.80 2.40 2.25 7,934 9,961 10,527 10,584 2.28 0.55 0.05Tajikistan 1,635 1,862 2,364 3,121 1.30 2.39 2.78 4,538 5,213 6,083 6,497 1.39 1.54 0.66Thailand 19,417 23,142 27,800 33,624 1.76 1.83 1.90 42,930 44,997 43,643 39,838 0.47 -0.31 -0.91Timor-Leste 198 329 538 848 5.08 4.92 4.55 617 842 1,080 1,277 3.11 2.49 1.68Turkey 43,027 52,728 62,033 70,247 2.03 1.63 1.24 23,433 22,977 21,840 20,128 -0.20 -0.51 -0.82Turkmenistan 2,062 2,562 3,175 3,793 2.17 2.15 1.78 2,440 2,614 2,642 2,483 0.69 0.11 -0.62United Arab Emirates 2,599 3,956 4,915 5,821 4.20 2.17 1.69 639 751 745 735 1.62 -0.08 -0.14Uzbekistan 9,273 10,075 11,789 14,500 0.83 1.57 2.07 15,502 17,720 19,396 19,433 1.34 0.90 0.02Viet Nam 19,263 27,046 36,269 46,585 3.39 2.93 2.50 59,400 61,983 61,743 58,862 0.43 -0.04 -0.48Yemen 4,776 7,714 12,082 17,844 4.79 4.49 3.90 13,406 16,542 19,553 21,506 2.10 1.67 0.95EUROPEAlbania 1,280 1,645 2,027 2,301 2.51 2.09 1.27 1,787 1,524 1,311 1,115 -1.59 -1.51 -1.62Andorra 61 76 85 96 2.20 1.12 1.22 5 10 15 17 6.93 4.05 1.25Austria 5,267 5,666 6,003 6,372 0.73 0.58 0.60 2,738 2,722 2,537 2,265 -0.06 -0.70 -1.13Belarus 7,030 7,162 7,219 7,070 0.19 0.08 -0.21 3,023 2,426 1,894 1,494 -2.20 -2.48 -2.37Belgium 9,899 10,421 10,792 11,070 0.51 0.35 0.25 294 277 256 233 -0.60 -0.79 -0.94Bosnia and Herzegovina 1,597 1,828 2,028 2,170 1.35 1.04 0.68 2,097 1,932 1,648 1,349 -0.82 -1.59 -2.00Bulgaria 5,516 5,357 5,215 5,012 -0.29 -0.27 -0.40 2,490 2,140 1,802 1,456 -1.51 -1.72 -2.13Channel Islands6 45 47 52 59 0.43 1.01 1.26 102 103 100 92 0.10 -0.30 -0.83Croatia 2,504 2,546 2,657 2,781 0.17 0.43 0.46 2,001 1,864 1,661 1,399 -0.71 -1.15 -1.72Czech Republic 7,565 7,656 7,929 8,202 0.12 0.35 0.34 2,660 2,755 2,639 2,318 0.35 -0.43 -1.30Denmark 4,540 4,761 4,923 5,058 0.48 0.33 0.27 795 720 634 558 -0.99 -1.27 -1.28Estonia 951 931 942 955 -0.21 0.12 0.14 419 409 390 347 -0.24 -0.48 -1.17Faeroe Islands 17 20 23 26 1.63 1.40 1.23 29 30 31 30 0.34 0.33 -0.33Finland7 4,252 4,549 4,805 4,947 0.68 0.55 0.29 922 797 691 597 -1.46 -1.43 -1.46France 45,466 53,398 58,267 61,043 1.61 0.87 0.47 13,662 9,238 6,664 5,431 -3.91 -3.27 -2.05Germany 59,970 60,598 60,827 60,993 0.10 0.04 0.03 22,105 21,458 19,595 16,862 -0.30 -0.91 -1.50Gibraltar 29 31 32 31 0.67 0.32 -0.32 — — — — — — —Greece 6,537 6,868 7,307 7,785 0.49 0.62 0.63 4,406 4,315 3,977 3,449 -0.21 -0.82 -1.42Holy See8 1 1 1 1 0.00 0.00 0.00 — — — — — — —Hungary 6,596 6,791 7,011 7,180 0.29 0.32 0.24 3,619 3,182 2,755 2,329 -1.29 -1.44 -1.68Iceland 260 308 349 372 1.69 1.25 0.64 21 22 21 20 0.47 -0.47 -0.49Ireland 2,250 2,842 3,370 3,889 2.34 1.70 1.43 1,554 1,747 1,775 1,684 1.17 0.16 -0.53Isle of Man 40 41 41 43 0.25 0.00 0.48 37 40 39 37 0.78 -0.25 -0.53Italy 38,395 41,083 42,840 44,395 0.68 0.42 0.36 18,721 19,015 17,569 15,154 0.16 -0.79 -1.48Latvia 1,616 1,517 1,471 1,453 -0.63 -0.31 -0.12 758 723 681 596 -0.47 -0.60 -1.33Liechtenstein 5 5 6 7 0.00 1.82 1.54 28 31 33 34 1.02 0.63 0.30Lithuania 2,345 2,181 2,096 2,080 -0.73 -0.40 -0.08 1,156 1,075 962 828 -0.73 -1.11 -1.50Luxembourg 366 419 480 547 1.35 1.36 1.31 71 73 70 67 0.28 -0.42 -0.44Malta 359 388 405 413 0.78 0.43 0.20 30 22 17 14 -3.10 -2.58 -1.94Moldova 1,828 1,679 1,833 1,938 -0.85 0.88 0.56 2,272 1,897 1,546 1,244 -1.80 -2.05 -2.17Monaco 32 33 34 35 0.31 0.30 0.29 — — — — — — —Montenegro 387 384 394 417 -0.08 0.26 0.57 274 241 237 217 -1.28 -0.17 -0.88Netherlands 12,222 13,799 14,824 15,501 1.21 0.72 0.45 3,692 2,854 2,319 1,997 -2.57 -2.08 -1.49Norway9 3,411 3,856 4,297 4,700 1.23 1.08 0.90 1,073 1,000 903 818 -0.70 -1.02 -0.99Poland 23,719 23,187 23,135 23,481 -0.23 -0.02 0.15 14,714 14,851 14,362 12,705 0.09 -0.33 -1.23Portugal 5,563 6,515 7,148 7,585 1.58 0.93 0.59 4,663 4,218 3,619 3,034 -1.00 -1.53 -1.76Romania 11,734 12,177 12,839 13,296 0.37 0.53 0.35 10,404 9,013 7,541 6,192 -1.44 -1.78 -1.97Russian Federation 107,582 102,702 100,892 99,153 -0.46 -0.18 -0.17 39,088 37,665 34,513 29,711 -0.37 -0.87 -1.50San Marino 25 30 31 32 1.82 0.33 0.32 2 2 2 2 0.00 0.00 0.00Serbia 5,369 5,525 5,871 6,252 0.29 0.61 0.63 4,765 4,331 3,911 3,392 -0.95 -1.02 -1.42Slovakia 3,025 2,975 3,031 3,168 -0.17 0.19 0.44 2,354 2,437 2,411 2,179 0.35 -0.11 -1.01Slovenia 1,008 1,002 1,035 1,110 -0.06 0.32 0.70 978 1,022 1,018 927 0.44 -0.04 -0.94

205Data Tables

TABLE B.2continued



2000 2010 2020 2030 2000– 2010– 2020– 2000 2010 2020 2030 2000– 2010– 2020–2010 2020 2030 2010 2020 2030

Spain 30,707 35,073 38,542 40,774 1.33 0.94 0.56 9,558 10,243 10,021 8,998 0.69 -0.22 -1.08Sweden 7,445 7,870 8,333 8,799 0.56 0.57 0.54 1,415 1,424 1,380 1,277 0.06 -0.31 -0.78Switzerland 5,268 5,591 5,922 6,336 0.60 0.58 0.68 1,917 2,003 1,957 1,812 0.44 -0.23 -0.77TFYR Macedonia10 1,194 1,212 1,260 1,331 0.15 0.39 0.55 818 831 785 685 0.16 -0.57 -1.36Ukraine 32,814 31,252 30,860 30,243 -0.49 -0.13 -0.20 16,056 14,181 12,085 9,946 -1.24 -1.60 -1.95United Kingdom 46,331 49,295 53,001 56,901 0.62 0.72 0.71 12,576 12,604 12,089 11,055 0.02 -0.42 -0.89LATIN AMERICA AND THE CARIBBEANAnguilla 11 15 18 19 3.10 1.82 0.54 — — — — — — —Antigua and Barbuda 25 27 32 40 0.77 1.70 2.23 52 62 66 65 1.76 0.63 -0.15Argentina 33,291 37,572 41,554 44,726 1.21 1.01 0.74 3,648 3,093 2,750 2,529 -1.65 -1.18 -0.84Aruba 42 50 54 59 1.74 0.77 0.89 48 57 57 53 1.72 0.00 -0.73Bahamas 250 291 331 367 1.52 1.29 1.03 55 55 54 51 0.00 -0.18 -0.57Barbados 97 114 134 151 1.61 1.62 1.19 155 142 128 110 -0.88 -1.04 -1.52Belize 120 164 213 268 3.12 2.61 2.30 131 149 161 162 1.29 0.77 0.06Bolivia 5,143 6,675 8,265 9,799 2.61 2.14 1.70 3,174 3,356 3,373 3,235 0.56 0.05 -0.42Brazil 141,416 169,098 187,104 197,874 1.79 1.01 0.56 32,759 26,326 21,947 19,272 -2.19 -1.82 -1.30British Virgin Islands 8 10 11 14 2.23 0.95 2.41 12 14 14 13 1.54 0.00 -0.74Cayman Islands 40 57 61 65 3.54 0.68 0.64 — — — — — — —Chile 13,252 15,251 16,958 18,247 1.40 1.06 0.73 2,167 1,884 1,681 1,532 -1.40 -1.14 -0.93Colombia 28,666 34,758 40,800 46,357 1.93 1.60 1.28 11,107 11,542 11,478 10,907 0.38 -0.06 -0.51Costa Rica 2,321 2,989 3,643 4,259 2.53 1.98 1.56 1,610 1,651 1,607 1,503 0.25 -0.27 -0.67Cuba 8,382 8,429 8,462 8,550 0.06 0.04 0.10 2,705 2,776 2,732 2,469 0.26 -0.16 -1.01Dominica 46 45 47 50 -0.22 0.43 0.62 22 22 21 18 0.00 -0.47 -1.54Dominican Republic 5,452 7,074 8,560 9,793 2.60 1.91 1.35 3,378 3,151 2,890 2,638 -0.70 -0.86 -0.91Ecuador 7,423 9,222 11,152 12,813 2.17 1.90 1.39 4,887 4,553 4,223 3,866 -0.71 -0.75 -0.88El Salvador 3,503 3,983 4,583 5,287 1.28 1.40 1.43 2,443 2,211 2,035 1,890 -1.00 -0.83 -0.74Falkland Islands (Malvinas) 2 2 2 3 0.00 0.00 4.05 1 1 1 1 0.00 0.00 0.00French Guiana 124 177 229 288 3.56 2.58 2.29 41 55 62 66 2.94 1.20 0.63Grenada 37 41 48 55 1.03 1.58 1.36 65 63 60 53 -0.31 -0.49 -1.24Guadeloupe 422 460 476 485 0.86 0.34 0.19 7 7 7 7 0.00 0.00 0.00Guatemala 5,068 7,111 9,893 13,153 3.39 3.30 2.85 6,163 7,266 8,198 8,539 1.65 1.21 0.41Guyana 217 218 233 265 0.05 0.67 1.29 539 544 512 449 0.09 -0.61 -1.31Haiti 3,079 5,307 7,546 9,450 5.44 3.52 2.25 5,569 4,881 4,177 3,746 -1.32 -1.56 -1.09Honduras 2,832 3,930 5,263 6,656 3.28 2.92 2.35 3,398 3,686 3,874 3,835 0.81 0.50 -0.10Jamaica 1,330 1,420 1,521 1,660 0.65 0.69 0.87 1,237 1,310 1,313 1,213 0.57 0.02 -0.79Martinique 345 362 370 376 0.48 0.22 0.16 40 44 45 42 0.95 0.22 -0.69Mexico 74,372 86,113 96,558 105,300 1.47 1.14 0.87 25,159 24,532 23,125 21,157 -0.25 -0.59 -0.89Montserrat 1 1 1 1 0.00 0.00 0.00 4 5 5 5 2.23 0.00 0.00Netherlands Antilles 163 187 199 200 1.37 0.62 0.05 18 14 11 9 -2.51 -2.41 -2.01Nicaragua 2,792 3,337 4,077 4,860 1.78 2.00 1.76 2,309 2,485 2,605 2,527 0.73 0.47 -0.30Panama 1,941 2,624 3,233 3,751 3.01 2.09 1.49 1,010 884 794 736 -1.33 -1.07 -0.76Paraguay 2,960 3,972 5,051 6,102 2.94 2.40 1.89 2,390 2,487 2,482 2,380 0.40 -0.02 -0.42Peru 18,994 22,688 26,389 29,902 1.78 1.51 1.25 7,010 6,808 6,492 6,103 -0.29 -0.48 -0.62Puerto Rico 3,614 3,949 4,112 4,178 0.89 0.40 0.16 204 49 23 18 -14.26 -7.56 -2.45Saint Kitts and Nevis 15 17 21 26 1.25 2.11 2.14 31 35 38 37 1.21 0.82 -0.27Saint Lucia 44 49 58 74 1.08 1.69 2.44 113 125 132 130 1.01 0.54 -0.15Saint Vincent and the Grenadines 49 54 60 68 0.97 1.05 1.25 59 55 50 44 -0.70 -0.95 -1.28Suriname 303 364 418 466 1.83 1.38 1.09 164 161 150 137 -0.18 -0.71 -0.91Trinidad and Tobago 140 186 250 328 2.84 2.96 2.72 1,155 1,157 1,133 1,054 0.02 -0.21 -0.72Turks and Caicos Islands 16 31 35 38 6.61 1.21 0.82 3 2 1 1 -4.05 -6.93 0.00United States Virgin Islands 101 104 102 96 0.29 -0.19 -0.61 8 5 4 3 -4.70 -2.23 -2.88Uruguay 3,033 3,119 3,264 3,382 0.28 0.45 0.36 288 254 229 206 -1.26 -1.04 -1.06Venezuela (Bolivarian Republic of) 21,940 27,113 31,755 35,588 2.12 1.58 1.14 2,468 1,931 1,658 1,556 -2.45 -1.52 -0.63NORTHERN AMERICABermuda 63 65 66 66 0.31 0.15 0.00 — — — — — — —Canada 24,389 27,309 30,426 33,680 1.13 1.08 1.02 6,298 6,581 6,675 6,416 0.44 0.14 -0.40Greenland 46 48 49 49 0.43 0.21 0.00 10 9 8 6 -1.05 -1.18 -2.88Saint-Pierre-et-Miquelon 6 5 6 6 -1.82 1.82 0.00 1 1 0 0 0.00 -1.00 0.00United States of America 227,651 261,375 293,732 321,698 1.38 1.17 0.91 60,191 56,266 52,421 48,283 -0.67 -0.71 -0.82OCEANIAAmerican Samoa 51 64 76 87 2.27 1.72 1.35 6 5 4 4 -1.82 -2.23 0.00Australia11 16,710 19,169 21,459 23,566 1.37 1.13 0.94 2,461 2,343 2,216 2,089 -0.49 -0.56 -0.59Cook Islands 11 15 17 19 3.10 1.25 1.11 6 5 4 3 -1.82 -2.23 -2.88Fiji 384 443 501 566 1.43 1.23 1.22 418 411 387 352 -0.17 -0.60 -0.95French Polynesia 124 140 160 186 1.21 1.34 1.51 112 132 144 143 1.64 0.87 -0.07Guam 144 168 188 208 1.54 1.12 1.01 11 12 13 13 0.87 0.80 0.00Kiribati 36 44 54 67 2.01 2.05 2.16 48 56 62 63 1.54 1.02 0.16Marshall Islands 36 45 56 65 2.23 2.19 1.49 16 18 18 18 1.18 0.00 0.00Micronesia (Federated States of) 24 25 29 38 0.41 1.48 2.70 83 86 88 87 0.36 0.23 -0.11Nauru 10 10 11 11 0.00 0.95 0.00 — — — — — — —New Caledonia 127 146 169 200 1.39 1.46 1.68 88 108 120 119 2.05 1.05 -0.08New Zealand 3,314 3,710 4,058 4,382 1.13 0.90 0.77 554 594 611 590 0.70 0.28 -0.35Niue 1 1 1 1 0.00 0.00 0.00 1 1 1 1 0.00 0.00 0.00Northern Mariana Islands 62 81 96 111 2.67 1.70 1.45 7 8 8 8 1.34 0.00 0.00Palau 13 17 20 23 2.68 1.63 1.40 6 3 2 2 -6.93 -4.05 0.00Papua New Guinea 711 863 1,194 1,828 1.94 3.25 4.26 4,676 6,026 7,275 8,230 2.54 1.88 1.23


TABLE B.2continued



2000 2010 2020 2030 2000– 2010– 2020– 2000 2010 2020 2030 2000– 2010– 2020–2010 2020 2030 2010 2020 2030

Pitcairn — — — — — — — — — — — — — —Samoa 39 36 38 46 -0.80 0.54 1.91 138 143 146 146 0.36 0.21 0.00Solomon Islands 65 99 152 230 4.21 4.29 4.14 350 436 510 558 2.20 1.57 0.90Tokelau — — — — — — — 2 1 1 1 -6.93 0.00 0.00Tonga 23 24 28 35 0.43 1.54 2.23 76 80 81 80 0.51 0.12 -0.12Tuvalu 4 5 6 7 2.23 1.82 1.54 5 5 5 4 0.00 0.00 -2.23Vanuatu 41 63 95 140 4.30 4.11 3.88 149 183 212 229 2.06 1.47 0.77Wallis and Futuna Islands — — — — — — — 15 15 17 17 0.00 1.25 0.00

Sources: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York.


207Data Tables

TABLE B.3Urbanization and Urban Slum Dwellers

Level of urbanization Urban slum dwellers

Estimates and projections Rate of change Estimate Rate of change(%) (%) ('000) (%)

2000 2010 2020 2030 2000– 2010– 2020– 1990 1995 2000 2005 2007 1990– 1995– 20002010 2020 2030 1995 2000 2005

AFRICAAlgeria 59.8 66.5 71.9 76.2 1.06 0.78 0.58 … … … … … … … …Angola 49.0 58.5 66.0 71.6 1.77 1.21 0.81 … … … 86.5 … … … …Benin 38.3 42.0 47.2 53.7 0.92 1.17 1.29 79.3 76.8 74.3 71.8 70.8 -0.64 -0.66 -0.68Botswana 53.2 61.1 67.6 72.7 1.38 1.01 0.73 … … … … … … … …Burkina Faso 17.8 25.7 34.4 42.8 3.67 2.92 2.18 78.8 72.4 65.9 59.5 59.5 -1.71 -1.87 -2.06Burundi 8.3 11.0 14.8 19.8 2.82 2.97 2.91 … … … 64.3 … … … …Cameroon 49.9 58.4 65.5 71.0 1.57 1.15 0.81 50.8 49.6 48.4 47.4 46.6 -0.49 -0.51 -0.40Cape Verde 53.4 61.1 67.4 72.5 1.35 0.98 0.73 … … … … … … … …Central African Republic 37.6 38.9 42.5 48.4 0.34 0.89 1.30 87.5 89.7 91.9 94.1 95.0 0.50 0.49 0.48Chad 23.4 27.6 33.9 41.2 1.65 2.06 1.95 98.9 96.4 93.9 91.3 90.3 -0.52 -0.53 -0.55Comoros 28.1 28.2 30.8 36.5 0.04 0.88 1.70 65.4 65.4 65.4 68.9 68.9 0.00 0.00 1.05Congo 58.3 62.1 66.3 70.9 0.63 0.65 0.67 … … … 53.4 … … … …Côte d'Ivoire 43.5 50.6 57.8 64.1 1.51 1.33 1.03 53.4 54.3 55.3 56.2 56.6 0.35 0.35 0.34Democratic Republic of the Congo 29.8 35.2 42.0 49.2 1.67 1.77 1.58 … … … 76.4 … … … …Djibouti 76.0 76.2 77.6 80.2 0.03 0.18 0.33 … … … … … … … …Egypt 42.8 43.4 45.9 50.9 0.14 0.56 1.03 50.2 39.2 28.1 17.1 17.1 -4.96 -6.62 -9.95Equatorial Guinea 38.8 39.7 43.3 49.4 0.23 0.87 1.32 … … … 66.3 … … … …Eritrea 17.8 21.6 27.5 34.4 1.93 2.41 2.24 … … … … … … … …Ethiopia 14.9 16.7 19.3 23.9 1.14 1.45 2.14 95.5 95.5 88.6 81.8 79.1 0.00 -1.48 -1.60Gabon 80.1 86.0 88.8 90.6 0.71 0.32 0.20 … … … 38.7 … … … …Gambia 49.1 58.1 65.0 71.0 1.68 1.12 0.88 … … … 45.4 … … … …Ghana 44.0 51.5 58.4 64.7 1.57 1.26 1.02 65.5 58.8 52.1 45.4 42.8 -2.15 -2.41 -2.74Guinea 31.0 35.4 41.4 48.6 1.33 1.57 1.60 80.4 68.8 57.3 45.7 45.7 -3.11 -3.68 -4.51Guinea-Bissau 29.7 30.0 32.8 38.6 0.10 0.89 1.63 … … … 83.1 … … … …Kenya 19.7 22.2 26.6 33.0 1.19 1.81 2.16 54.9 54.8 54.8 54.8 54.8 -0.01 -0.01 -0.01Lesotho 20.0 26.9 34.5 42.4 2.96 2.49 2.06 35.1 35.1 35.1 35.1 35.1 0.00 0.00 0.00Liberia 44.3 47.8 52.1 57.6 0.76 0.86 1.00 … … … … … … … …Libyan Arab Jamahiriya 76.4 77.9 80.3 82.9 0.19 0.30 0.32 … … … … … … … …Madagascar 27.1 30.2 34.9 41.4 1.08 1.45 1.71 93.0 88.6 84.1 80.6 78.0 -0.97 -1.02 -0.86Malawi 15.2 19.8 25.5 32.4 2.64 2.53 2.39 66.4 66.4 66.4 66.4 67.7 0.00 0.00 0.00Mali 28.3 35.9 43.7 51.3 2.38 1.97 1.60 94.2 84.8 75.4 65.9 65.9 -2.11 -2.36 -2.67Mauritania 40.0 41.4 45.4 51.7 0.34 0.92 1.30 … … … … … … … …Mauritius1 42.7 41.8 43.4 48.0 -0.21 0.38 1.01 … … … … … … … …Mayotte 47.7 50.1 51.6 55.7 0.48 0.30 0.77 … … … … … … … …Morocco 53.3 58.2 64.0 69.2 0.88 0.95 0.78 37.4 35.2 24.2 13.1 13.1 -1.21 -7.54 -12.23Mozambique 30.7 38.4 46.3 53.7 2.24 1.87 1.48 75.6 76.9 78.2 79.5 80.0 0.34 0.33 0.33Namibia 32.4 38.0 44.4 51.5 1.59 1.56 1.48 34.4 34.1 33.9 33.9 33.6 -0.13 -0.14 -0.01Niger 16.2 17.1 19.3 23.5 0.54 1.21 1.97 83.6 83.1 82.6 82.1 81.9 -0.12 -0.12 -0.12Nigeria 42.5 49.8 56.8 63.6 1.59 1.32 1.13 77.3 73.5 69.6 65.8 64.2 -1.02 -1.08 -1.14Réunion 89.9 94.0 95.7 96.3 0.45 0.18 0.06 … … … … … … … …Rwanda 13.8 18.9 22.6 28.3 3.14 1.79 2.25 96.0 87.9 79.7 71.6 68.3 -1.77 -1.95 -2.16Saint Helena2 39.7 39.7 41.7 46.4 0.00 0.49 1.07 … … … … … … … …São Tomé and Príncipe 53.4 62.2 69.0 74.0 1.53 1.04 0.70 … … … … … … … …Senegal 40.3 42.4 46.5 52.5 0.51 0.92 1.21 70.6 59.8 48.9 38.1 38.1 -3.33 -4.00 -5.01Seychelles 51.0 55.3 61.1 66.6 0.81 1.00 0.86 … … … … … … …Sierra Leone 35.5 38.4 42.8 49.0 0.79 1.08 1.35 … … … 97.0 … … … …Somalia 33.2 37.4 43.0 49.9 1.19 1.40 1.49 … … … 73.5 … … … …South Africa 56.9 61.7 66.6 71.3 0.81 0.76 0.68 46.2 39.7 33.2 28.7 28.7 -3.03 -3.58 -2.91Sudan 33.4 40.1 47.4 54.5 1.83 1.67 1.40 … … … 94.2 … … … …Swaziland 22.6 21.4 22.3 26.2 -0.55 0.41 1.61 … … … … … … … …Togo 36.5 43.4 50.5 57.3 1.73 1.52 1.26 … … … 62.1 … … … …Tunisia 63.4 67.3 71.2 75.2 0.60 0.56 0.55 … … … … … … … …Uganda 12.1 13.3 15.9 20.6 0.95 1.79 2.59 75.0 75.0 75.0 66.7 63.4 0.00 0.00 -2.35United Republic of Tanzania 22.3 26.4 31.8 38.7 1.69 1.86 1.96 77.4 73.7 70.1 66.4 65.0 -0.97 -1.01 -1.07Western Sahara 83.9 81.8 83.9 85.9 -0.25 0.25 0.24 … … … … … … … …Zambia 34.8 35.7 38.9 44.7 0.26 0.86 1.39 57.0 57.1 57.2 57.2 57.3 0.02 0.02 0.01Zimbabwe 33.8 38.3 43.9 50.7 1.25 1.36 1.44 4.0 3.7 3.3 17.9 17.9 -1.56 -2.11 33.64ASIAAfghanistan 20.2 22.6 26.4 32.2 1.12 1.55 1.99 … … … … … … … …Armenia 64.7 64.2 65.7 69.0 -0.08 0.23 0.49 … … … … … … … …Azerbaijan 51.2 51.9 54.2 58.6 0.14 0.43 0.78 … … … … … … … …Bahrain 88.4 88.6 89.4 90.6 0.02 0.09 0.13 … … … … … … … …Bangladesh 23.6 28.1 33.9 41.0 1.75 1.88 1.90 87.3 84.7 77.8 70.8 70.8 -0.60 -1.71 -1.87Bhutan 25.4 34.7 42.4 50.0 3.12 2.00 1.65 … … … … … … … …Brunei Darussalam 71.1 75.7 79.3 82.3 0.63 0.46 0.37 … … … … … … … …Cambodia 16.9 20.1 23.8 29.2 1.73 1.69 2.04 … … … 78.9 … … … …China3 35.8 47.0 55.0 61.9 2.72 1.57 1.18 43.6 40.5 37.3 32.9 31.0 -1.49 -1.61 -2.52China, Hong Kong SAR4 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …China, Macao SAR5 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Cyprus 68.6 70.3 72.7 75.7 0.24 0.34 0.40 … … … … … … … …Democratic People's Republic of Korea 59.4 60.2 62.1 65.7 0.13 0.31 0.56 … … … … … … … …Georgia 52.6 52.7 54.7 58.7 0.02 0.37 0.71 … … … … … … … …India 27.7 30.0 33.9 39.7 0.80 1.22 1.58 54.9 48.2 41.5 34.8 32.1 -2.61 -3.00 -3.53Indonesia 42.0 44.3 48.1 53.7 0.53 0.82 1.10 50.8 42.6 34.4 26.3 23.0 -3.51 -4.26 -5.42Iran (Islamic Republic of) 64.2 70.8 75.9 79.8 0.98 0.70 0.50 16.9 16.9 16.9 52.8 52.8 0.00 0.00 22.77


TABLE B.3continued



2000 2010 2020 2030 2000– 2010– 2020– 1990 1995 2000 2005 2007 1990– 1995– 20002010 2020 2030 1995 2000 2005

Iraq 67.8 66.2 66.6 69.4 -0.24 0.06 0.41 … … … … … … … …Israel 91.4 91.9 92.4 93.1 0.05 0.05 0.08 … … … … … … … …Japan 65.2 66.8 69.4 73.0 0.24 0.38 0.51 … … … … … … … …Jordan 78.3 78.5 79.8 82.0 0.03 0.16 0.27 … … … 15.8 … … … …Kazakhstan 56.3 58.5 62.3 66.8 0.38 0.63 0.70 … … … … … … … …Kuwait 98.2 98.4 98.6 98.7 0.02 0.02 0.01 … … … … … … … …Kyrgyzstan 35.2 34.5 35.7 40.1 -0.20 0.34 1.16 … … … … … … … …Lao People's Democratic Republic 22.0 33.2 44.2 53.1 4.12 2.86 1.83 … … … 79.3 … … … …Lebanon 86.0 87.2 88.6 90.0 0.14 0.16 0.16 … … … 53.1 … … … …Malaysia 62.0 72.2 78.5 82.2 1.52 0.84 0.46 … … … … … … … …Maldives 27.7 40.1 51.5 60.1 3.70 2.50 1.54 … … … … … … … …Mongolia 56.9 62.0 67.0 71.6 0.86 0.78 0.66 68.5 66.7 64.9 57.9 57.9 -0.53 -0.55 -2.28Myanmar 27.8 33.6 40.7 48.1 1.89 1.92 1.67 … … … 45.6 … … … …Nepal 13.4 18.6 24.8 31.7 3.28 2.88 2.45 70.6 67.3 64.0 60.7 59.4 -0.96 -1.00 -1.06Occupied Palestinian Territory 72.0 74.1 76.6 79.4 0.29 0.33 0.36 … … … … … … … …Oman 71.6 73.0 75.7 78.7 0.19 0.36 0.39 … … … … … … … …Pakistan 33.1 35.9 39.9 45.6 0.81 1.06 1.34 51.0 49.8 48.7 47.5 47.0 -0.46 -0.47 -0.49Philippines 48.0 48.9 52.6 58.3 0.19 0.73 1.03 54.3 50.8 47.2 43.7 42.3 -1.35 -1.45 -1.56Qatar 94.9 95.8 96.5 96.9 0.09 0.07 0.04 … … … … … … … …Republic of Korea 79.6 83.0 85.6 87.7 0.42 0.31 0.24 … … … … … … … …Saudi Arabia 79.8 82.1 84.2 86.2 0.28 0.25 0.23 … … … 18.0 … … … …Singapore 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Sri Lanka 15.8 14.3 15.5 19.6 -1.00 0.81 2.35 … … … … … … … …Syrian Arab Republic 51.9 55.7 60.2 65.4 0.71 0.78 0.83 … … … 10.5 … … … …Tajikistan 26.5 26.3 28.0 32.5 -0.08 0.63 1.49 … … … … … … … …Thailand 31.1 34.0 38.9 45.8 0.89 1.35 1.63 … … … 26.0 … … … …Timor-Leste 24.3 28.1 33.2 39.9 1.45 1.67 1.84 … … … … … … … …Turkey 64.7 69.6 74.0 77.7 0.73 0.61 0.49 23.4 20.7 17.9 15.5 14.1 -2.49 -2.84 -2.91Turkmenistan 45.8 49.5 54.6 60.4 0.78 0.98 1.01 … … … … … … … …United Arab Emirates 80.3 84.1 86.8 88.8 0.46 0.32 0.23 … … … … … … … …Uzbekistan 37.4 36.2 37.8 42.7 -0.33 0.43 1.22 … … … … … … … …Viet Nam 24.5 30.4 37.0 44.2 2.16 1.96 1.78 60.5 54.6 48.8 41.3 38.3 -2.04 -2.27 -3.33Yemen 26.3 31.8 38.2 45.3 1.90 1.83 1.70 … … … 67.2 … … … …EUROPEAlbania 41.7 51.9 60.7 67.4 2.19 1.57 1.05 … … … … … … … …Andorra 92.4 88.0 84.9 85.1 -0.49 -0.36 0.02 … … … … … … … …Austria 65.8 67.6 70.3 73.8 0.27 0.39 0.49 … … … … … … … …Belarus 69.9 74.7 79.2 82.6 0.66 0.58 0.42 … … … … … … … …Belgium 97.1 97.4 97.7 97.9 0.03 0.03 0.02 … … … … … … … …Bosnia and Herzegovina 43.2 48.6 55.2 61.7 1.18 1.27 1.11 … … … … … … … …Bulgaria 68.9 71.5 74.3 77.5 0.37 0.38 0.42 … … … … … … … …Channel Islands6 30.5 31.4 34.2 39.1 0.29 0.85 1.34 … … … … … … … …Croatia 55.6 57.7 61.5 66.5 0.37 0.64 0.78 … … … … … … … …Czech Republic 74.0 73.5 75.0 78.0 -0.07 0.20 0.39 … … … … … … … …Denmark 85.1 86.9 88.6 90.1 0.21 0.19 0.17 … … … … … … … …Estonia 69.4 69.5 70.7 73.4 0.01 0.17 0.37 … … … … … … … …Faeroe Islands 36.3 40.3 42.2 46.6 1.05 0.46 0.99 … … … … … … … …Finland7 82.2 85.1 87.4 89.2 0.35 0.27 0.20 … … … … … … … …France 76.9 85.3 89.7 91.8 1.04 0.50 0.23 … … … … … … … …Germany 73.1 73.8 75.6 78.3 0.10 0.24 0.35 … … … … … … … …Gibraltar 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Greece 59.7 61.4 64.8 69.3 0.28 0.54 0.67 … … … … … … … …Holy See8 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Hungary 64.6 68.1 71.8 75.5 0.53 0.53 0.50 … … … … … … … …Iceland 92.4 93.4 94.3 95.0 0.11 0.10 0.07 … … … … … … … …Ireland 59.1 61.9 65.5 69.8 0.46 0.57 0.64 … … … … … … … …Isle of Man 51.8 50.6 51.2 53.9 -0.23 0.12 0.51 … … … … … … … …Italy 67.2 68.4 70.9 74.6 0.18 0.36 0.51 … … … … … … … …Latvia 68.1 67.7 68.4 70.9 -0.06 0.10 0.36 … … … … … … … …Liechtenstein 15.1 14.3 15.0 18.0 -0.54 0.48 1.82 … … … … … … … …Lithuania 67.0 67.0 68.5 71.5 0.00 0.22 0.43 … … … … … … … …Luxembourg 83.8 85.2 87.4 89.1 0.17 0.25 0.19 … … … … … … … …Malta 92.4 94.7 96.0 96.6 0.25 0.14 0.06 … … … … … … … …Moldova 44.6 47.0 54.2 60.9 0.52 1.43 1.17 … … … … … … … …Monaco 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Montenegro 58.5 61.5 62.4 65.7 0.50 0.15 0.52 … … … … … … … …Netherlands 76.8 82.9 86.5 88.6 0.76 0.43 0.24 … … … … … … … …Norway9 76.1 79.4 82.6 85.2 0.42 0.40 0.31 … … … … … … … …Poland 61.7 61.0 61.7 64.9 -0.11 0.11 0.51 … … … … … … … …Portugal 54.4 60.7 66.4 71.4 1.10 0.90 0.73 … … … … … … … …Romania 53.0 57.5 63.0 68.2 0.81 0.91 0.79 … … … … … … … …Russian Federation 73.4 73.2 74.5 76.9 -0.03 0.18 0.32 … … … … … … … …San Marino 93.4 94.1 94.4 94.9 0.07 0.03 0.05 … … … … … … … …Serbia 53.0 56.1 60.0 64.8 0.57 0.67 0.77 … … … … … … … …Slovakia 56.2 55.0 55.7 59.2 -0.22 0.13 0.61 … … … … … … … …Slovenia 50.8 49.5 50.4 54.5 -0.26 0.18 0.78 … … … … … … … …

209Data Tables

TABLE B.3continued



2000 2010 2020 2030 2000– 2010– 2020– 1990 1995 2000 2005 2007 1990– 1995– 20002010 2020 2030 1995 2000 2005

Spain 76.3 77.4 79.4 81.9 0.14 0.26 0.31 … … … … … … … …Sweden 84.0 84.7 85.8 87.3 0.08 0.13 0.17 … … … … … … … …Switzerland 73.3 73.6 75.2 77.8 0.04 0.22 0.34 … … … … … … … …TFYR Macedonia10 59.4 59.3 61.6 66.0 -0.02 0.38 0.69 … … … … … … … …Ukraine 67.1 68.8 71.9 75.3 0.25 0.44 0.46 … … … … … … … …United Kingdom 78.7 79.6 81.4 83.7 0.11 0.22 0.28 … … … … … … … …LATIN AMERICA AND THE CARIBBEANAnguilla 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Antigua and Barbuda 32.1 30.3 32.5 38.4 -0.58 0.70 1.67 … … … … … … … …Argentina 90.1 92.4 93.8 94.6 0.25 0.15 0.08 30.5 31.7 32.9 26.2 23.5 0.77 0.74 -4.55Aruba 46.7 46.9 48.8 52.5 0.04 0.40 0.73 … … … … … … … …Bahamas 82.0 84.1 86.1 87.9 0.25 0.24 0.21 … … … … … … … …Barbados 38.3 44.5 51.1 57.9 1.50 1.38 1.25 … … … … … … … …Belize 47.8 52.2 56.9 62.3 0.88 0.86 0.91 … … … 47.3 … … … …Bolivia 61.8 66.5 71.0 75.2 0.73 0.65 0.57 62.2 58.2 54.3 50.4 48.8 -1.30 -1.40 -1.50Brazil 81.2 86.5 89.5 91.1 0.63 0.34 0.18 36.7 34.1 31.5 29.0 28.0 -1.45 -1.56 -1.69British Virgin Islands 39.4 41.0 45.2 51.6 0.40 0.98 1.32 … … … … … … … …Cayman Islands 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Chile 85.9 89.0 91.0 92.3 0.35 0.22 0.14 … … … 9.0 … … … …Colombia 72.1 75.1 78.0 81.0 0.41 0.38 0.38 31.2 26.8 22.3 17.9 16.1 -3.07 -3.62 -4.43Costa Rica 59.0 64.4 69.4 73.9 0.88 0.75 0.63 … … … 10.9 … … … …Cuba 75.6 75.2 75.6 77.6 -0.05 0.05 0.26 … … … … … … … …Dominica 67.2 67.2 69.4 73.1 0.00 0.32 0.52 … … … … … … … …Dominican Republic 61.7 69.2 74.8 78.8 1.15 0.78 0.52 27.9 24.4 21.0 17.6 16.2 -2.63 -3.03 -3.57Ecuador 60.3 66.9 72.5 76.8 1.04 0.80 0.58 … … … 21.5 … … … …El Salvador 58.9 64.3 69.3 73.7 0.88 0.75 0.62 … … … 28.9 … … … …Falkland Islands (Malvinas) 67.6 73.6 78.2 81.6 0.85 0.61 0.43 … … … … … … … …French Guiana 75.1 76.4 78.6 81.4 0.17 0.28 0.35 … … … 10.5 … … … …Grenada 35.9 39.3 44.5 51.2 0.90 1.24 1.40 … … … 6.0 … … … …Guadeloupe 98.4 98.4 98.5 98.6 0.00 0.01 0.01 … … … 5.4 … … … …Guatemala 45.1 49.5 54.7 60.6 0.93 1.00 1.02 58.6 53.3 48.1 42.9 40.8 -1.87 -2.06 -2.30Guyana 28.7 28.6 31.3 37.2 -0.03 0.90 1.73 … … … 33.7 … … … …Haiti 35.6 52.1 64.4 71.6 3.81 2.12 1.06 93.4 93.4 93.4 70.1 70.1 0.00 0.00 -5.74Honduras 45.5 51.6 57.6 63.4 1.26 1.10 0.96 … … … 34.9 … … … …Jamaica 51.8 52.0 53.7 57.8 0.04 0.32 0.74 … … … 60.5 … … … …Martinique 89.7 89.0 89.1 90.0 -0.08 0.01 0.10 … … … … … … … …Mexico 74.7 77.8 80.7 83.3 0.41 0.37 0.32 23.1 21.5 19.9 14.4 14.4 -1.44 -1.55 -6.47Montserrat 11.0 14.3 16.9 21.6 2.62 1.67 2.45 … … … … … … … …Netherlands Antilles 90.2 93.2 94.7 95.5 0.33 0.16 0.08 … … … … … … … …Nicaragua 54.7 57.3 61.0 65.8 0.46 0.63 0.76 89.1 74.5 60.0 45.5 45.5 -3.56 -4.34 -5.55Panama 65.8 74.8 80.3 83.6 1.28 0.71 0.40 … … … 23.0 … … … …Paraguay 55.3 61.5 67.1 71.9 1.06 0.87 0.69 … … … 17.6 … … … …Peru 73.0 76.9 80.3 83.0 0.52 0.43 0.33 66.4 56.3 46.2 36.1 36.1 -3.30 -3.96 -4.94Puerto Rico 94.6 98.8 99.5 99.6 0.43 0.07 0.01 … … … … … … … …Saint Kitts and Nevis 32.8 32.4 35.4 41.6 -0.12 0.89 1.61 … … … … … … … …Saint Lucia 28.0 28.0 30.6 36.1 0.00 0.89 1.65 … … … 11.9 … … … …Saint Vincent and the Grenadines 45.2 49.3 54.6 60.7 0.87 1.02 1.06 … … … … … … … …Suriname 64.9 69.4 73.5 77.3 0.67 0.57 0.50 … … … 3.9 … … … …Trinidad and Tobago 10.8 13.9 18.1 23.7 2.52 2.64 2.70 … … … 24.7 … … … …Turks and Caicos Islands 84.6 93.3 96.5 97.4 0.98 0.34 0.09 … … … … … … … …United States Virgin Islands 92.6 95.3 96.5 97.0 0.29 0.13 0.05 … … … … … … … …Uruguay 91.3 92.5 93.4 94.3 0.13 0.10 0.10 … … … … … … … …Venezuela (Bolivarian Republic of) 89.9 93.4 95.0 95.8 0.38 0.17 0.08 … … … 32.0 … … … …NORTHERN AMERICABermuda 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …Canada 79.5 80.6 82.0 84.0 0.14 0.17 0.24 … … … … … … … …Greenland 81.6 84.2 86.5 88.4 0.31 0.27 0.22 … … … … … … … …Saint-Pierre-et-Miquelon 89.1 90.6 91.8 92.8 0.17 0.13 0.11 … … … … … … … …United States of America 79.1 82.3 84.9 87.0 0.40 0.31 0.24 … … … … … … … …OCEANIAAmerican Samoa 88.8 93.0 94.8 95.6 0.46 0.19 0.08 … … … … … … … …Australia11 87.2 89.1 90.6 91.9 0.22 0.17 0.14 … … … … … … … …Cook Islands 65.2 75.3 81.4 84.9 1.44 0.78 0.42 … … … … … … … …Fiji 47.9 51.9 56.4 61.7 0.80 0.83 0.90 … … … … … … … …French Polynesia 52.4 51.4 52.7 56.6 -0.19 0.25 0.71 … … … … … … … …Guam 93.1 93.2 93.5 94.2 0.01 0.03 0.07 … … … … … … … …Kiribati 43.0 43.9 46.5 51.7 0.21 0.58 1.06 … … … … … … … …Marshall Islands 68.4 71.8 75.3 78.8 0.49 0.48 0.45 … … … … … … … …Micronesia (Federated States of) 22.3 22.7 25.1 30.3 0.18 1.01 1.88 … … … … … … … …Nauru 100.0 100.0 100.0 100.0 0.00 0.00 0.00 … … … … … … … …New Caledonia 59.2 57.4 58.5 62.7 -0.31 0.19 0.69 … … … … … … … …New Zealand 85.7 86.2 86.9 88.1 0.06 0.08 0.14 … … … … … … … …Niue 33.1 37.5 43.0 49.4 1.25 1.37 1.39 … … … … … … … …Northern Mariana Islands 90.2 91.3 92.4 93.3 0.12 0.12 0.10 … … … … … … … …Palau 70.0 83.4 89.6 92.0 1.75 0.72 0.26 … … … … … … … …Papua New Guinea 13.2 12.5 14.1 18.2 -0.54 1.20 2.55 … … … … … … … …


TABLE B.3continued



2000 2010 2020 2030 2000– 2010– 2020– 1990 1995 2000 2005 2007 1990– 1995– 20002010 2020 2030 1995 2000 2005

Pitcairn 0.0 0.0 0.0 0.0 0.00 0.00 0.00 … … … … … … … …Samoa 22.0 20.2 20.5 24.0 -0.85 0.15 1.58 … … … … … … … …Solomon Islands 15.7 18.6 23.0 29.2 1.70 2.12 2.39 … … … … … … … …Tokelau 0.0 0.0 0.0 0.0 0.00 0.00 0.00 … … … … … … … …Tonga 23.0 23.4 25.6 30.4 0.17 0.90 1.72 … … … … … … … …Tuvalu 46.0 50.4 55.6 61.5 0.91 0.98 1.01 … … … … … … … …Vanuatu 21.7 25.6 31.0 38.0 1.65 1.91 2.04 … … … … … … … …Wallis and Futuna Islands 0.0 0.0 0.0 0.0 0.00 0.00 0.00 … … … … … … … …

Sources: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York; United Nations Human Settlements Programme (UN-Habitat), Urban Info 2010.


211Data Tables

TABLE B.4Access to Drinking Water and Sanitation

Improved drinking water coverage Household connection to improved drinking water Improved sanitation coverage

Total Urban Rural Total Urban Rural Total Urban Rural(%) (%) (%) (%) (%) (%) (%) (%) (%)

1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008

AFRICAAlgeria 94 83 100 85 88 79 68 72 87 80 48 56 88 95 99 98 77 88Angola 36 50 30 60 40 38 0 20 1 34 0 1 25 57 58 86 6 18Benin 56 75 72 84 47 69 7 12 19 26 0 2 5 12 14 24 1 4Botswana 93 95 100 99 88 90 24 62 39 80 13 35 36 60 58 74 20 39Burkina Faso 41 76 73 95 36 72 2 4 12 21 0 0 6 11 28 33 2 6Burundi 70 72 97 83 68 71 3 6 32 47 1 1 44 46 41 49 44 46Cameroon 50 74 77 92 31 51 11 15 25 25 2 3 47 47 65 56 35 35Cape Verde … 84 … 85 … 82 … 38 … 46 … 27 … 54 … 65 … 38Central African Republic 58 67 78 92 47 51 3 2 8 6 0 0 11 34 21 43 5 28Chad 38 50 48 67 36 44 2 5 10 17 0 1 6 9 20 23 2 4Comoros1 87 95 98 91 83 97 16 30 31 53 10 21 17 36 34 50 11 30Congo … 71 … 95 … 34 … 28 … 43 … 3 … 30 … 31 … 29Côte d'Ivoire 76 80 90 93 67 68 22 40 49 67 5 14 20 23 38 36 8 11Democratic Republic of the Congo 45 46 90 80 27 28 14 9 51 23 0 2 9 23 23 23 4 23Djibouti 77 92 80 98 69 52 57 72 69 82 19 3 66 56 73 63 45 10Egypt 90 99 96 100 86 98 61 92 90 99 39 87 72 94 91 97 57 92Equatorial Guinea … … … … … … 4 … 12 … 0 0 … … … … … …Eritrea 43 61 62 74 39 57 6 9 40 42 0 0 9 14 58 52 0 4Ethiopia 17 38 77 98 8 26 1 7 10 40 0 0 4 12 21 29 1 8Gabon … 87 … 95 … 41 … 43 … 49 … 10 … 33 … 33 … 30Gambia 77 92 85 96 67 86 9 33 24 55 0 5 … 67 … 68 … 65Ghana 54 82 84 90 37 74 16 17 41 30 2 3 7 13 11 18 4 7Guinea 52 71 87 89 38 61 6 10 21 26 0 1 9 19 18 34 6 11Guinea-Bissau … 61 … 83 37 51 2 9 6 27 0 1 … 21 … 49 … 9Kenya 43 59 91 83 32 52 19 19 57 44 10 12 26 31 24 27 27 32Lesotho 61 85 88 97 57 81 4 19 19 59 1 5 32 29 29 40 32 25Liberia 58 68 86 79 34 51 11 2 21 3 3 0 11 17 21 25 3 4Libyan Arab Jamahiriya 54 … 54 … 55 … … … … …. … … 97 97 97 97 96 96Madagascar 31 41 78 71 16 29 6 7 25 14 0 4 8 11 14 15 6 10Malawi 40 80 90 95 33 77 7 7 45 26 2 2 42 56 50 51 41 57Mali 29 56 54 81 22 44 4 12 17 34 0 1 26 36 36 45 23 32Mauritania 30 49 36 52 26 47 6 22 15 34 0 14 16 26 29 50 8 9Mauritius 99 99 100 100 99 99 99 99 100 100 99 99 91 91 93 93 90 90Mayotte2 … … … … … … … … … … … … … … … … … …Morocco 74 81 94 98 55 60 38 58 74 88 5 19 53 69 81 83 27 52Mozambique 36 47 73 77 26 29 5 8 22 20 1 1 11 17 36 38 4 4Namibia 64 92 99 99 51 88 33 44 82 72 14 27 25 33 66 60 9 17Niger 35 48 57 96 31 39 3 7 21 37 0 1 5 9 19 34 2 4Nigeria 47 58 79 75 30 42 14 6 32 11 4 2 37 32 39 36 36 28Réunion … … … … … … … … … … … … … … … … … …Rwanda 68 65 96 77 66 62 2 4 32 15 0 1 23 54 35 50 22 55Saint Helena … … … … … … … … … … … … … … … … … …São Tomé and Príncipe … 89 … 89 … 88 … 26 … 32 … 18 … 26 … 30 … 19Senegal 61 69 88 92 43 52 19 38 45 74 3 12 38 51 62 69 22 38Seychelles … … … 100 … … … … … 100 … … … … … 97 … …Sierra Leone … 49 … 86 … 26 … 6 … 15 1 1 … 13 … 24 … 6Somalia … 30 … 67 … 9 … 19 … 51 0 0 … 23 … 52 … 6South Africa 83 91 98 99 66 78 56 67 85 89 25 32 69 77 80 84 58 65Sudan 65 57 85 64 58 52 34 28 76 47 19 14 34 34 63 55 23 18Swaziland … 69 … 92 … 61 … 32 … 67 … 21 … 55 … 61 … 53Togo 49 60 79 87 36 41 4 6 14 12 0 1 13 12 25 24 8 3Tunisia 81 94 95 99 62 84 61 76 89 94 22 39 74 85 95 96 44 64Uganda 43 67 78 91 39 64 1 3 9 19 0 1 39 48 35 38 40 49United Republic of Tanzania 55 54 94 80 46 45 7 8 34 23 1 3 24 24 27 32 23 21Western Sahara … … … … … … … … … … … … … … … … … …Zambia 49 60 89 87 23 46 20 14 49 37 1 1 46 49 62 59 36 43Zimbabwe 78 82 99 99 70 72 32 36 94 88 7 5 43 44 58 56 37 37ASIAAfghanistan … 48 … 78 … 39 … 4 … 16 … 0 … 37 … 60 … 30Armenia … 96 99 98 … 93 84 87 96 97 59 70 … 90 95 95 … 80Azerbaijan 70 80 88 88 49 71 44 50 67 78 17 20 … 45 … 51 … 39Bahrain … … 100 100 … … … … 100 100 … … … … 100 100 … …Bangladesh 78 80 88 85 76 78 6 6 28 24 0 0 39 53 59 56 34 52Bhutan … 92 … 99 … 88 … 57 … 81 … 45 … 65 … 87 … 54Brunei Darussalam … … … … … … … … … … … … … … … … … …Cambodia 35 61 52 81 33 56 2 16 17 55 0 5 9 29 38 67 5 18China 67 89 97 98 56 82 54 83 86 96 42 73 41 55 48 58 38 52China, Hong Kong SAR … … … … … … … … … … … … … … … … … …China, Macao SAR … … … … … … … … … … … … … … … … … …Cyprus 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100Democratic People's Republic of Korea 100 100 100 100 100 100 … … … … … … … … … … … …Georgia 81 98 94 100 66 96 53 73 81 92 19 51 96 95 97 96 95 93India 72 88 90 96 66 84 19 22 52 48 8 11 18 31 49 54 7 21Indonesia 71 80 92 89 62 71 9 23 24 37 2 8 33 52 58 67 22 36Iran (Islamic Republic of) 91 … 98 98 84 … 84 … 96 96 69 … 83 … 86 … 78 …Iraq 81 79 97 91 44 55 … 76 … 90 … 49 … 73 … 76 … 66


TABLE B.4continued



1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008

Israel 100 100 100 100 100 100 100 100 100 100 98 98 100 100 100 100 100 100Japan 100 100 100 100 100 100 93 98 97 99 86 95 100 100 100 100 100 100Jordan 97 96 99 98 91 91 95 91 98 94 87 79 … 98 98 98 … 97Kazakhstan 96 95 99 99 92 90 63 58 91 82 28 24 96 97 96 97 97 98Kuwait 99 99 99 99 99 99 … … … … … … 100 100 100 100 100 100Kyrgyzstan … 90 98 99 … 85 44 54 75 89 25 34 … 93 94 94 … 93Lao People's Democratic Republic … 57 … 72 … 51 … 20 … 55 … 4 … 53 … 86 … 38Lebanon 100 100 100 100 100 100 … … 100 100 … … … … 100 100 … …Malaysia 88 100 94 100 82 99 72 97 86 99 59 91 84 96 88 96 81 95Maldives 90 91 100 99 87 86 12 37 47 95 0 2 69 98 100 100 58 96Mongolia 58 76 81 97 27 49 30 19 52 32 0 2 … 50 … 64 … 32Myanmar 57 71 87 75 47 69 5 6 19 15 1 2 … 81 … 86 … 79Nepal 76 88 96 93 74 87 8 17 43 52 5 10 11 31 41 51 8 27Occupied Palestinian Territory … 91 100 91 … 91 … 78 … 84 … 64 … 89 … 91 … 84Oman 80 88 84 92 72 77 21 54 29 68 6 18 85 … 97 97 61 …Pakistan 86 90 96 95 81 87 24 33 57 55 9 20 28 45 73 72 8 29Philippines 84 91 93 93 76 87 24 48 40 60 8 25 58 76 70 80 46 69Qatar 100 100 100 100 100 100 … … … … … … 100 100 100 100 100 100Republic of Korea … 98 97 100 … 88 … 93 96 99 … 64 100 100 100 100 100 100Saudi Arabia 89 … 97 97 63 … 88 … 97 97 60 … … … 100 100 … …Singapore 100 100 100 100 .. .. 100 100 100 100 .. .. 99 100 99 100 .. ..Sri Lanka 67 90 91 98 62 88 11 28 37 65 6 22 70 91 85 88 67 92Syrian Arab Republic 85 89 96 94 75 84 72 83 93 93 51 71 83 96 94 96 72 95Tajikistan … 70 … 94 … 61 … 40 … 83 … 25 … 94 93 95 … 94Thailand 91 98 97 99 89 98 33 54 78 85 14 39 80 96 93 95 74 96Timor-Leste … 69 … 86 … 63 … 16 … 28 … 1 … 50 … 76 … 40Turkey 85 99 94 100 73 96 76 96 91 98 54 92 84 90 96 97 66 75Turkmenistan … … 97 97 … … … … … … … … 98 98 99 99 97 97United Arab Emirates 100 100 100 100 100 100 … 78 … 80 … 70 97 97 98 98 95 95Uzbekistan 90 87 97 98 85 81 57 48 86 85 37 26 84 100 95 100 76 100Viet Nam 58 94 88 99 51 92 9 22 45 56 0 9 35 75 61 94 29 67Yemen … 62 … 72 … 57 … 28 … 54 … 17 18 52 64 94 6 33EUROPEAlbania … 97 100 96 … 98 … 86 98 91 … 82 … 98 … 98 … 98Andorra 100 100 100 100 100 100 … …. 100 100 … … 100 100 100 100 100 100Austria 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100Belarus 100 100 100 100 99 99 … 89 … 95 … 72 … 93 … 91 … 97Belgium 100 100 100 100 100 100 100 100 100 100 96 100 100 100 100 100 100 100Bosnia and Herzegovina … 99 … 100 … 98 … 82 … 94 … 71 … 95 … 99 … 92Bulgaria 100 100 100 100 99 100 88 … 96 96 72 … 99 100 100 100 98 100Channel Islands … … … … … … … … … … … … … … … … … …Croatia … 99 … 100 … 97 … 88 … 96 … 77 … 99 … 99 … 98Czech Republic 100 100 100 100 100 100 … 95 97 97 … 91 100 98 100 99 98 97Denmark 100 100 100 100 100 100 100 … 100 … 100 100 100 100 100 100 100 100Estonia 98 98 99 99 97 97 80 90 92 97 51 75 … 95 … 96 … 94Faeroe Islands … … … … … … … … … … … … … … … … … …Finland 100 100 100 100 100 100 92 … 96 100 85 … 100 100 100 100 100 100France 100 100 100 100 100 100 99 100 100 100 95 100 100 100 100 100 100 100Germany 100 100 100 100 100 100 99 99 100 100 97 97 100 100 100 100 100 100Gibraltar … … … … … … … … … … … … … … … … … …Greece 96 100 99 100 92 99 92 100 99 100 82 99 97 98 100 99 92 97Holy See … … … … … … … … … … … … … … … … … …Hungary 96 100 98 100 91 100 86 94 94 95 72 93 100 100 100 100 100 100Iceland 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100Ireland 100 100 100 100 100 100 100 100 100 100 99 99 99 99 100 100 98 98Isle of Man … … … … … … … … … … … … … … … … … …Italy 100 100 100 100 100 100 99 100 100 100 96 100 … … … … … …Latvia 99 99 100 100 96 96 … 82 … 93 … 59 … 78 … 82 … 71Liechtenstein … … … … … … … … … … … … … … … … … …Lithuania … … … … … … 76 … 89 … 49 … … … … … … …Luxembourg 100 100 100 100 100 100 100 100 100 100 98 98 100 100 100 100 100 100Malta 100 100 100 100 98 100 100 100 100 100 98 100 100 100 100 100 100 100Moldova … 90 … 96 … 85 … 40 … 79 … 13 … 79 … 85 … 74Monaco 100 100 100 100 .. .. 100 100 100 100 .. .. 100 100 100 100 .. ..Montenegro … 98 … 100 … 96 … 85 … 98 … 66 … 92 … 96 … 86Netherlands 100 100 100 100 100 100 98 100 100 100 95 100 100 100 100 100 100 100Norway 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100Poland 100 100 100 100 100 100 88 98 97 99 73 96 … 90 96 96 … 80Portugal 96 99 98 99 94 100 87 99 95 99 80 100 92 100 97 100 87 100Romania … … … … … … 47 61 85 91 3 26 71 72 88 88 52 54Russian Federation 93 96 98 98 81 89 76 78 87 92 45 40 87 87 93 93 70 70San Marino … … … … … … … … … … … … … … … … … …Serbia … 99 … 99 … 98 … 81 … 97 … 63 … 92 … 96 … 88Slovakia … 100 … 100 … 100 95 94 100 94 89 94 100 100 100 100 100 99Slovenia 100 99 100 100 99 99 100 99 100 100 99 99 100 100 100 100 100 100Spain 100 100 100 100 100 100 99 99 99 99 100 100 100 100 100 100 100 100Sweden 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

213Data Tables

TABLE B.4continued



1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008

Switzerland 100 100 100 100 100 100 100 100 100 100 99 99 100 100 100 100 100 100TFYR Macedonia3 … 100 … 100 … 99 … 92 … 96 … 84 … 89 … 92 … 82Ukraine … 98 99 98 … 97 … 67 93 87 … 25 95 95 97 97 91 90United Kingdom 100 100 100 100 100 100 100 100 100 100 98 98 100 100 100 100 100 100LATIN AMERICA AND THE CARIBBEANAnguilla … … … … .. .. … … … … .. .. 99 99 99 99 .. ..Antigua and Barbuda … … 95 95 … … … … … … … … … … 98 98 … …Argentina 94 97 97 98 72 80 69 80 76 83 22 45 90 90 93 91 73 77Aruba 100 100 100 100 100 100 100 100 100 100 100 100 … … … … … …Bahamas … … 98 98 … … … … … … … … 100 100 100 100 100 100Barbados 100 100 100 100 100 100 … … 98 100 … … 100 100 100 100 100 100Belize 75 99 85 99 63 100 47 74 77 87 20 61 74 90 73 93 75 86Bolivia 70 86 92 96 42 67 50 77 78 93 14 47 19 25 29 34 6 9Brazil 88 97 96 99 65 84 78 91 92 96 35 62 69 80 81 87 35 37British Virgin Islands 98 98 98 98 98 98 97 97 97 97 97 97 100 100 100 100 100 100Cayman Islands … 95 … 95 .. .. 37 92 37 92 .. .. 96 96 96 96 .. ..Chile 90 96 99 99 48 75 84 93 97 99 22 47 84 96 91 98 48 83Colombia 88 92 98 99 68 73 86 84 98 94 59 56 68 74 80 81 43 55Costa Rica 93 97 99 100 86 91 82 96 92 100 71 89 93 95 94 95 91 96Cuba 82 94 93 96 53 89 64 75 77 82 30 54 80 91 86 94 64 81Dominica … … … … … … … … … … … … … … … … … …Dominican Republic 88 86 98 87 76 84 73 72 94 80 46 54 73 83 83 87 61 74Ecuador 72 94 81 97 62 88 47 88 66 96 24 74 69 92 86 96 48 84El Salvador 74 87 90 94 58 76 43 65 72 80 14 42 75 87 88 89 62 83Falkland Islands (Malvinas) … … … … … … … … … … … … … … … … … …French Guiana … … … … … … … … … … … … … … … … … …Grenada … … 97 97 … … … … … … … … 97 97 96 96 97 97Guadeloupe … … 98 98 … … … … 98 98 … … … … … 95 … …Guatemala 82 94 91 98 75 90 49 81 68 95 35 68 65 81 84 89 51 73Guyana … 94 … 98 … 93 … 67 … 76 … 63 … 81 … 85 … 80Haiti 47 63 62 71 41 55 9 12 27 21 2 4 26 17 44 24 19 10Honduras 72 86 91 95 59 77 58 83 82 94 42 72 44 71 68 80 28 62Jamaica 93 94 98 98 88 89 61 70 89 91 33 47 83 83 82 82 83 84Martinique … … 100 100 … … … … 99 99 … … … … … 95 … …Mexico 85 94 94 96 64 87 77 87 88 92 50 72 66 85 80 90 30 68Montserrat 100 100 100 100 100 100 12 15 98 98 0 0 96 96 96 96 96 96Netherlands Antilles … … … … … … … … … … … … … … … … … …Nicaragua 74 85 92 98 54 68 52 62 83 88 18 27 43 52 59 63 26 37Panama 84 93 99 97 66 83 80 89 97 93 60 79 58 69 73 75 40 51Paraguay 52 86 81 99 25 66 29 65 59 85 0 35 37 70 61 90 15 40Peru 75 82 88 90 45 61 55 70 73 84 15 35 54 68 71 81 16 36Puerto Rico … … … … … … … … … … … … … … … … … …Saint Kitts and Nevis 99 99 99 99 99 99 … … … … … … 96 96 96 96 96 96Saint Lucia 98 98 98 98 98 98 … … … … … … … … … … … …Saint Vincent and the Grenadines … … … … … … … … … … … … … … … … … …Suriname … 93 99 97 … 81 … 70 94 78 … 45 … 84 90 90 … 66Trinidad and Tobago 88 94 92 98 88 93 69 76 81 88 68 74 93 92 93 92 93 92Turks and Caicos Islands 100 100 100 100 100 100 … … … … … … … … 98 98 … …United States Virgin Islands … … … … … … … … … … … … … … … … … …Uruguay 96 100 98 100 79 100 89 98 94 98 50 92 94 100 95 100 83 99Venezuela (Bolivarian Republic of) 90 … 93 … 71 … 80 … 87 … 44 … 82 … 89 … 45 …NORTHERN AMERICABermuda … … … … … … … … … … … … … … … … … …Canada 100 100 100 100 99 99 … … 100 100 … … 100 100 100 100 99 99Greenland … … … … … … … … … … … … … … … … … …Saint-Pierre-et-Miquelon … … … … … … … … … … … … … … … … 96 96United States of America 99 99 100 100 94 94 84 88 97 97 46 46 100 100 100 100 99 99OCEANIAAmerican Samoa … … … … … … … … … … … … … … … … … …Australia 100 100 100 100 100 100 … … … … … … 100 100 100 100 100 100Cook Islands 94 … 99 98 87 … … … … … … … 96 100 100 100 91 100Fiji … … 92 … … … … … … … … … … … 92 … … …French Polynesia 100 100 100 100 100 100 98 98 99 99 96 96 98 98 99 99 97 97Guam 100 100 100 100 100 100 … … … … … … 99 99 99 99 98 98Kiribati 48 … 76 … 33 … 25 … 46 … 13 … 26 … 36 … 21 …Marshall Islands 95 94 94 92 97 99 … 1 … 1 … 0 64 73 77 83 41 53Micronesia (Federated States of) 89 … 93 95 87 … … … … … … … 29 … 55 … 20 …Nauru … 90 … 90 .. .. … … … … .. .. … 50 … 50 .. ..New Caledonia … … … … … … … … … … … … … … … … … …New Zealand 100 100 100 100 100 100 100 100 100 100 100 100 … … … … 88 …Niue 100 100 100 100 100 100 … … … … … … 100 100 100 100 100 100Northern Mariana Islands 98 98 98 98 100 97 … … … … … … 84 … 85 … 78 96Palau 81 … 73 … 98 … … … … … … … 69 … 76 96 54 …Papua New Guinea 41 40 89 87 32 33 13 10 61 57 4 3 47 45 78 71 42 41Pitcairn … … … … … … … … … … … … … … … … … …Samoa 91 … 99 … 89 … … … … … … … 98 100 100 100 98 100Solomon Islands … … … … … … … … 76 … … … … … 98 98 … …


TABLE B.4continued



1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008 1990 2008

Tokelau 90 97 .. .. 90 97 … … .. .. … … 41 93 .. .. 41 93Tonga … 100 … 100 … 100 … … … … … … 96 96 98 98 96 96Tuvalu 90 97 92 98 89 97 … 97 … 97 … 97 80 84 86 88 76 81Vanuatu 57 83 91 96 49 79 37 44 79 79 27 33 … 52 … 66 … 48Wallis and Futuna Islands 100 100 .. .. 100 100 80 81 .. .. 80 81 96 96 .. .. 96 96

Source: World Health Organization (WHO) and United Nations Children’s Fund (UNICEF) Joint Monitoring Programme for Water Supply and Sanitation (JMP) (2010) Progress on Sanitation and Drinking-Water 2010 Update,WHO and UNICEF, Geneva.

Notes:(1) This includes the island of Mayotte.(2) Data for Mayotte is included in the data on Comoros.(3) The former Yugoslav Republic of Macedonia.

215Data Tables

TABLE B.5Poverty and Inequality

Gross national income Inequality National poverty line International poverty linePPP $/capita

Income / Land Population Populationconsumption

2000 20081 Survey Gini Survey Gini Survey Rural Urban National Survey Below Belowyear2 index year index year % % % year3 US$1.25/day US$2/day

AFRICAAlgeria 5,120 7,890 1995 0.35 … 1995 30.3 14.7 22.6 1995 6.8 23.6Angola 1,850 4,830 2000 0.59 … … … … 2000 54.3 70.2Benin 1,120 1,470 2003 0.37 … 2003 46.0 29.0 39.0 2003 47.3 75.3Botswana 8,340 13,310 1993-94 0.61 … … … … 1993-94 31.2 49.4Burkina Faso 810 1,160 2003 0.40 1993 0.42 2003 52.4 19.2 46.4 2003 56.5 81.2Burundi 310 380 2006 0.33 … … … … 2006 81.3 93.4Cameroon 1,520 2,170 2001 0.45 … 200711 55.0 12.2 39.9 2001 32.8 57.7Cape Verde 1,970 3,090 2001 0.50 … … … … 2001 20.6 40.2Central African Republic 660 730 2003 0.44 … … … … 2003 62.4 81.9Chad 640 1,070 2002-03 0.40 … … … … 2002-03 61.9 83.3Comoros 970 1,170 2004 0.64 … … … … 2004 46.1 65.0Congo 2,020 2,810 2005 0.47 … … … … 2005 54.1 74.4Côte d'Ivoire 1,430 1,580 2002 0.48 … … … … 2002 23.3 46.8Democratic Republic of the Congo 200 280 … … … … … 2005-06 59.2 79.5Djibouti 1,600 2,320 2002 0.40 … … … … 2002 18.8 41.2Egypt 3,570 5,470 2004-05 0.32 1990 0.65 1999-2000 … … 16.7 2004-05 <2 18.4Equatorial Guinea 5,330 21,720 … … … … … … …Eritrea 610 6405 … … … … … … …Ethiopia 460 870 2005 0.30 2001 0.47 1999-2000 45.0 37.0 44.2 2005 39.0 77.5Gabon 9,940 12,400 2005 0.42 … … … … 2005 4.8 19.6Gambia 920 1,280 2003 0.47 … 2003 63.0 57.0 61.3 2003 34.3 56.7Ghana 900 1,320 2006 0.43 … 2005-06 39.2 10.8 28.5 2006 30.0 53.6Guinea 760 970 2003 0.43 … 1994 … … 40.0 2003 70.1 87.2Guinea-Bissau 480 520 2002 0.36 1988 0.62 … … … 2002 48.8 77.9Kenya 1,120 1,560 2005-06 0.48 … 2005/06 49.7 34.4 46.6 2005-06 19.7 39.9Lesotho 1,320 1,970 2002-03 0.53 1989-90 0.49 2002/0311 60.5 41.5 56.3 2002-03 43.4 62.2Liberia 290 310 2007 0.53 … … … … 2007 83.7 94.8Libyan Arab Jamahiriya … 16,270 … … … … … … …Madagascar 790 1,050 2005 0.47 … 200511 53.5 52.0 68.7 2005 67.8 89.6Malawi 600 810 2004-05 0.39 1993 0.52 2004-05 55.9 25.4 52.4 2004-0514 73.9 90.4Mali 710 1,100 2006 0.39 … … … … 2006 51.4 77.1Mauritania 1,410 … 2000 0.39 … 2000 61.2 25.4 46.3 2000 21.2 44.1Mauritius 8,040 12,580 … … … … … … …Mayotte … … … … … … … … …Morocco 2,510 4,190 2007 0.41 1996 0.62 1998-99 27.2 12.0 19.0 2007 2.5 14.0Mozambique 420 770 2002-03 0.47 … 2002-03 54.1 51.6 55.2 2002-03 74.7 90.0Namibia 4,160 6,250 19939 0.74 1997 0.36 … … … 199315 49.1 62.2Niger 500 680 2005 0.44 … 1989-93 66.0 52.0 63.0 2005 65.9 85.6Nigeria 1,130 1,980 2003-04 0.43 … 1992-93 36.4 30.4 34.1 2003-04 64.4 83.9Réunion … … … … … … … … …Rwanda 580 1,110 2000 0.47 … 2005-0611 62.5 … 56.9 2000 76.6 90.3Saint Helena … … … … … … … … …São Tomé and Príncipe … 1,790 2000-01 0.51 … … … … 2000-01 28.4 56.6Senegal 1,270 1,780 2005 0.39 1998 0.50 1992 40.4 23.7 33.4 2005 33.5 60.3Seychelles 15,310 19,650 2006-07 0.02 … … … … 2006-07 <2 <2Sierra Leone 360 770 2003 0.43 … 2003-04 79.0 56.4 70.2 2003 53.4 76.1Somalia … … … … … … … … …South Africa 6,470 9,790 2000 0.58 … 200811 … … 22.0 2000 26.2 42.9Sudan 1,070 1,920 … … … … … … …Swaziland 3,650 5,000 2000-01 0.51 … … … … 2000-01 62.9 81.0Togo 690 830 2006 0.34 … … … 2006 38.7 69.3Tunisia 4,590 7,460 2000 0.41 1993 0.70 1995 13.9 3.6 7.6 2000 2.6 12.8Uganda 680 1,140 2005 0.43 1991 0.59 2005-0611 34.2 13.7 31.1 2005 51.5 75.6United Republic of Tanzania 770 1,2606 2000-01 0.35 … 2000-01 38.7 29.5 35.7 2000-01 88.5 96.6Western Sahara … …7 … … … … … … …Zambia 840 1,230 2004-05 0.51 … 2004 78.0 53.0 68.0 2004-05 64.3 81.5Zimbabwe 210 … 1995 0.50 … 1995-96 48.0 7.9 34.9 … …ASIAAfghanistan … 1,1005 … … 2007 45.0 27.0 42.0 … …Armenia 2,090 6,310 2007 0.30 … 2001 48.7 51.9 50.9 2007 3.7 21.0Azerbaijan 2,060 7,770 2005 0.17 … 2001 42.0 55.0 49.6 2005 <2 <2Bahrain 20,030 33,430 … … … … … … …Bangladesh 820 1,450 2005 0.31 1996 0.62 2005 43.8 28.4 40.0 2005 49.6 81.317

Bhutan 2,330 4,820 2003 0.47 … … … … 2003 26.2 49.5Brunei Darussalam 42,050 … … … … … … … …Cambodia 860 1,870 2007 0.44 … 2007 34.7 .. 30.1 2007 25.8 57.8China 2,330 6,010 20059 0.42 … 200611 2.5 … … 2005 15.9 36.318

China, Hong Kong SAR 26,520 44,000 19969 0.43 … … … … … …China, Macao SAR 20,250 … … … … … … … …Cyprus 18,710 24,980 … … … … … … …Democratic People's Republic of Korea … … … … … … … … …Georgia 2,140 4,920 2005 0.41 … 2003 52.7 56.2 54.5 2005 13.4 30.4India 1,500 2,930 2004-05 0.37 … 1999-2000 30.2 24.7 28.6 2004-05 41.6 75.618

Indonesia 2,200 3,600 2007 0.38 1993 0.46 2004 20.1 12.1 16.7 2007 29.4 60.0


TABLE B.5continued




Iran (Islamic Republic of) 6,790 … 2005 0.38 … … … … 2005 <2 8.0Iraq … … … … … … … … …Israel 21,480 27,450 20019 0.39 … … … … … …Japan 25,950 35,190 19939 0.25 1995 0.59 … … … … …Jordan 3,240 5,720 2006 0.38 1997 0.78 2002 18.7 12.9 14.2 2006 <2 3.5Kazakhstan 4,450 9,720 2007 0.31 … 2002 … … 15.4 2007 <2 <2Kuwait 35,410 … … … … … … … …Kyrgyzstan 1,250 2,150 2007 0.34 … 2005 50.8 29.8 43.1 2007 3.4 27.5Lao People's Democratic Republic 1,130 2,050 2002-03 0.33 1999 0.39 2002-03 … … 33.5 2002-03 44.0 76.817

Lebanon 7,710 11,750 … … … … … … …Malaysia 8,350 13,740 20049 0.38 … 1989 … … 15.5 2004 15 <2 7.8Maldives 2,920 5,290 2004 0.37 … … … … … …Mongolia 1,790 3,470 2007-08 0.37 … 2002 43.4 30.3 36.1 2007-08 2.2 13.6Myanmar … … … … … … … … …Nepal 800 1,120 2003-04 0.47 1992 0.45 2003-04 34.6 9.6 30.9 2003-04 55.1 77.6Occupied Palestinian Territory … … … … … … … … …Oman 15,100 … … … … … … … …Pakistan 1,690 2,590 2004-05 0.31 1990 0.57 1998-99 35.9 24.2 32.6 2004-05 22.6 60.3Philippines 2,430 3,900 2006 0.44 1991 0.55 1997 36.9 11.9 25.1 2006 22.6 45.0Qatar … … 2006-07 0.41 … … … … … …Republic of Korea 17,130 27,840 19989 0.32 1990 0.34 … … … … …Saudi Arabia 17,500 24,500 … … … … … … …Singapore 32,870 47,970 19989 0.43 … … … … … …Sri Lanka 2,660 4,460 2002 0.41 … 2002 7.9 24.7 22.7 2002 14.0 39.7Syrian Arab Republic 3,150 4,490 … … … … … … …Tajikistan 800 1,870 2004 0.34 … 2007 55.0 49.4 53.5 2004 21.5 50.8Thailand 4,850 7,770 2004 0.43 1993 0.47 1998 … … 13.6 2004 <2 11.5Timor-Leste 790 4,6905 2007 0.32 … … … … 2007 37.2 72.8Turkey 8,730 13,420 2006 0.41 1991 0.61 2002 34.5 22.0 27.0 2006 2.6 8.2Turkmenistan 1,930 6,130 1998 0.41 … … … … 1998 24.8 49.6United Arab Emirates 41,610 … … … … … … … …Uzbekistan 1,420 2,6605 2003 0.37 … 2003 29.8 22.6 27.2 … …Viet Nam 1,390 2,700 2006 0.38 1994 0.53 2002 35.6 6.6 28.9 2006 21.5 48.4Yemen 1,710 2,220 2005 0.38 … 1998 45.0 30.8 41.8 2005 17.5 46.6EUROPEAlbania 4,100 7,520 2005 0.33 1998 0.84 2005 24.2 11.2 18.5 2005 <2 7.8Andorra … … … … … … … … …Austria 28,290 37,360 20009 0.29 1999-2000 0.59 … … … … …Belarus 5,120 12,120 2007 0.29 … 2004 … … 17.4 2007 <2 <2Belgium 28,180 35,380 20009 0.33 1999-2000 0.56 … … … … …Bosnia and Herzegovina 4,620 8,360 2007 0.36 … … … … 2007 <2 <2Bulgaria 6,180 11,370 2003 0.29 … 2001 … … 12.8 2003 <2 <2Channel Islands … … … … … … … …Croatia 10,910 17,050 2005 0.29 … 2004 … … 11.1 2005 <2 <2Czech Republic 14,650 22,890 19969 0.26 2000 0.92 … … … 199615 <2 <2Denmark 28,220 37,530 19979 0.25 1999-2000 0.51 … … … … …Estonia 9,530 19,320 2004 0.36 2001 0.79 … … … 2004 <2 <2Faeroe Islands … … … … … … … … …Finland 25,490 35,940 20009 0.27 1999-2000 0.27 … … … … …France 25,680 33,280 19959 0.33 1999-2000 0.58 … … … … …Germany 25,700 35,950 20009 0.28 1999-2000 0.63 … … … … …Gibraltar … … … … … … … … …Greece 18,460 28,300 20009 0.34 1999-2000 0.58 … … … … …Holy See … … … … … … … … …Hungary 11,740 18,210 2004 0.30 … 1997 … … 17.3 2004 <2 <2Iceland 28,060 25,300 … … … … … … …Ireland 24,690 35,710 20009 0.34 … … … … … …Isle of Man … … … … … … … … …Italy 25,400 30,800 20009 0.36 1999-2000 0.73 … … … … …Latvia 8,260 16,010 2007 0.36 2001 0.58 2004 12.7 … 5.9 2007 <2 <2Liechtenstein … … … … … … … … …Lithuania 8,720 17,170 2004 0.36 … … … … 2004 <2 <2Luxembourg 46,750 52,770 … 1999-2000 0.48 … … … … …Malta 18,380 … … … … … … … …Moldova 1,490 3,2708 2007 0.37 … 2002 67.2 42.6 48.5 2007 2.4 11.5Monaco … … 2007-08 0.37 … … … … … …Montenegro 5,940 13,420 2007 0.37 … … … … 2007 <2 <2Netherlands 30,040 40,620 19999 0.31 1999-2000 0.57 … … … … …Norway 35,640 59,250 20009 0.26 1999 0.18 … … … … …Poland 10,470 16,710 2005 0.35 2002 0.69 2001 … … 14.8 2005 <2 <2Portugal 16,670 22,330 19979 0.39 1999-2000 0.74 … … … … …Romania 5,780 13,380 2007 0.32 … 2002 … … 28.9 2007 <2 4.1Russian Federation 7,420 15,460 2007 0.44 … 2002 … … 19.6 2007 <2 <2San Marino … … … … … … … … …Serbia 5,630 10,380 2008 0.28 … … … … 2008 <2 <2

217Data Tables

TABLE B.5continued




Slovakia 10,810 21,460 19969 0.26 … … … … 199615 <2 <2Slovenia 17,490 27,160 2004 0.31 1991 0.62 … … … 2004 <2 <2Spain 21,140 30,830 20009 0.35 1999-2000 0.77 … … … … …Sweden 27,530 37,780 20009 0.25 1999-2000 0.32 … … … … …Switzerland 34,060 39,210 20009 0.34 1999 0.50 … … … … …TFYR Macedonia4 6,030 9,250 2006 0.43 … 2003 22.3 … 21.7 2006 <2 5.3Ukraine 3,170 7,210 2008 0.28 … 2003 28.4 … 19.5 2008 <2 <2United Kingdom 26,020 36,240 19999 0.36 1999-2000 0.66 … … … … …LATIN AMERICA AND THE CARIBBEANAnguilla … … … … … … … … …Antigua and Barbuda 11,420 19,660 … … … … … … …Argentina 8,850 14,000 20069,10 0.49 1988 0.83 200111 … 35.9 … 200410,15 4.5 11.3Aruba … … … … … … … … …Bahamas … … … … … … … … …Barbados … … … … … … … … …Belize 4,630 5,9405 1995 0.60 … … … … … …Bolivia 2,930 4,140 2007 0.57 … 2007 63.9 23.7 37.7 200716 11.9 21.9Brazil 6,810 10,080 20079 0.55 1996 0.85 2002-03 41.0 17.5 21.5 200715 5.2 12.7British Virgin Islands … … … … … … … … …Cayman Islands … … … … … … … … …Chile 8,910 13,250 20069 0.52 … 200611 … … 13.7 200615 <2 2.4Colombia 5,550 8,430 20069 0.59 2001 0.80 2006 62.1 39.1 45.1 200615 16.0 27.9Costa Rica 6,610 10,960 20079 0.49 … 2004 28.3 20.8 23.9 200715 <2 4.3Cuba … … … … … … … … …Dominica 5,300 8,300 … … … … … … …Dominican Republic 4,760 7,8005 20079 0.48 … 200711 54.1 45.4 48.5 200715 4.4 12.3Ecuador 4,430 7,780 20079 0.54 … 200611 61.5 24.9 38.3 200715 4.7 12.8El Salvador 4,500 6,6305 20079 0.47 … 200612 36.0 27.8 30.7 200715 6.4 13.2Falkland Islands (Malvinas) … … … … … … … … …French Guiana … … … … … … … … …Grenada 5,910 8,4305 … … … … … … …Guadeloupe … … … … … … … … …Guatemala 3,460 4,6905 20069 0.54 … 2006 72.0 28.0 51.0 200615 11.7 24.3Guyana 1,980 3,030 19989 0.43 … … … … 199815 7.7 16.8Haiti … … 20019 0.60 … 1995 66.0 … … 200115 54.9 72.1Honduras 2,490 3,8305 20069 0.55 1993 0.66 2004 70.4 29.5 50.7 200615 18.2 29.7Jamaica 5,560 7,370 2004 0.46 … 2000 25.1 12.8 18.7 2004 <2 5.8Martinique … … … … … … … … …Mexico 8,960 14,340 20089 0.52 … 2004 56.9 41.0 47.0 200815 4.0 8.2Montserrat … … … … … … … … …Netherlands Antilles … … … … … … … … …Nicaragua 1,780 2,6205 20059 0.52 2001 0.72 2001 64.3 28.7 45.8 200515 15.8 31.8Panama 6,830 12,630 20069 0.55 2001 0.52 2003 … … 36.8 200615 9.5 17.8Paraguay 3,360 4,660 20079 0.53 1991 0.93 199013 28.5 19.7 20.5 200715 6.5 14.2Peru 4,750 7,950 20079 0.51 1994 0.86 2004 72.5 40.3 51.6 200715 7.7 17.8Puerto Rico … … … … … … … … …Saint Kitts and Nevis 9,720 15,490 … … … … … … …Saint Lucia 6,860 9,0205 19959 0.43 … … … … 199515 20.9 40.6Saint Vincent and the Grenadines 5,010 8,570 … … … … … … …Suriname 4,400 6,6805 19999 0.53 … … … … 199915 15.5 27.2Trinidad and Tobago 10,790 24,240 19929 0.40 … 1992 20.0 24.0 21.0 199215 4.2 13.5Turks and Caicos Islands … … … … … … … … …United States Virgin Islands … … … … … … … … …Uruguay 8,170 12,550 20079 0.47 2000 0.79 1998 … 24.7 … 200715 <2 4.3Venezuela (Bolivarian Republic of) 8,360 12,850 20069 0.43 1996-97 0.88 1997-99 … … 52.0 200615 3.5 10.2NORTHERN AMERICABermuda … … … … … … … … …Canada 27,670 38,710 20009 0.33 1991 0.64 … … … … …Greenland … … … … … … … … …Saint-Pierre-et-Miquelon … … … … … … … … …United States of America 35,190 46,790 20009 0.41 1997 0.76 … … … … …OCEANIAAmerican Samoa … … … … … … … … …Australia 26,690 37,250 19949 0.35 … … … … … …Cook Islands … … … … … … … … …Fiji 3,500 4,320 … … … … … … …French Polynesia … … … … … … … … …Guam … … … … … … … … …Kiribati 3,100 3,620 … … … … … … …Marshall Islands … … … … … … … … …Micronesia (Federated States of) 2,830 3,2705 2000 0.01 … … … … … …Nauru … … … … … … … … …New Caledonia … … … … … … … … …


TABLE B.5continued




New Zealand 19,450 25,200 19979 0.36 … … … … … …Niue … … … … … … … … …Northern Mariana Islands … … … … … … … … …Palau … … … … … … … … …Papua New Guinea 1,620 2,0305 1996 0.51 … 1996 41.3 16.1 37.5 1996 35.8 57.4Pitcairn … … … … … … … … …Samoa 2,810 4,4105 … … … … … … …Solomon Islands 1,970 2,230 … … … … … … …Tokelau … … … … … … … … …Tonga 2,960 3,9805 … … … … … … …Tuvalu … … … … … … … … …Vanuatu 2,930 … … … … … … … …Wallis and Futuna Islands … … … … … … … … …

Sources: World Bank (2010) World Development Indicators 2010, World Bank, Washington, DC; World Bank (2006) World Development Report 2006, World Bank, Washington, DC.

Notes:(1) Data are extrapolated from the 2005 International Comparison Program benchmark estimates, unless otherwise specified.(2) Data refers to expenditure shares by percentiles of population, ranked by per capita expenditure, unless otherwise specfied.(3) Data are expenditure based unless otherwise specified.(4) The former Yugoslav Republic of Macedonia.(5) Estimate is based on regression.(6) Data covers mainland Tanzania only.(7) Data for Western Sahara is included in the data on Morocco.(8) Data excludes Transnistria.(9) Data refers to income shares by percentiles of population, ranked by per capita income.(10) Data includes urban areas only.(11) Data are from national sources.(12) Data refers to share of households rather than share of population.(13) Data covers Asuncion metropolitan area only.(14) Due to change in survey design, the most recent survey is not strictly comparable with the previous one.(15) Data is income based.(16) In purchasing power parity (PPP) dollars imputed using regression.(17) Refers to data adjusted by spatial consumer price index information.(18) Data covers weighted average of urban and rural estimates.

219Data Tables

TABLE B.6Transport Infrastructure

Roads Motor vehicles Railways

Total Paved Passengers Goods hauled Number per Route Passengers Goods hauled(km) (%) (m-p-km) (m-t-km) 1000 population (km) (m-p-km) (m-t-km)

2000–20071 2000–20071 2000–20071 2000–20071 1990 2007 2000–20081 2000–20081 2000–20081

AFRICAAlgeria 108,302 70.2 … … 55 91 3,572 937 1,562Angola 51,429 10.4 166,045 4,709 19 40 … … …Benin 19,000 9.5 … … 3 21 758 … 36Botswana 25,798 33.2 … … 18 113 888 94 674Burkina Faso 92,495 4.2 … … 4 11 622 … …Burundi 12,322 10.4 … … … 6 … … …Cameroon 51,346 8.4 … … 10 … 977 379 978Cape Verde … … … … … … … … …Central African Republic 24,307 … … … 1 0 … … …Chad 40,000 0.8 … … 2 6 … … …Comoros … … … … … … … … …Congo 17,289 5.0 … … 18 26 795 211 234Côte d'Ivoire 80,000 8.1 … … 24 … 639 … 675Democratic Republic of the Congo 153,497 1.8 … … … 5 4,007 95 352Djibouti … … … … … … … … …Egypt 92,370 81.0 … … 29 … 5,063 40,830 4,188Equatorial Guinea … … … … … … … … …Eritrea 4,010 21.8 … … 1 11 … … …Ethiopia 42,429 12.8 219,113 2,456 1 3 … … …Gabon 9,170 10.2 … … 32 … 810 99 2,502Gambia 3,742 19.3 16 … 13 7 … … …Ghana 57,614 14.9 … … 8 33 953 85 181Guinea 44,348 9.8 … … 4 … … … …Guinea-Bissau 3,455 27.9 … … 7 33 … … …Kenya 63,265 14.1 … 22 12 21 1,917 250 1,399Lesotho 5,940 18.3 … … 11 … … … …Liberia 10,600 6.2 … … 14 3 … … …Libyan Arab Jamahiriya 83,200 57.2 … … … 291 … … …Madagascar 49,827 11.6 … … 6 … 854 10 1Malawi 15,451 45.0 … … 4 9 797 44 33Mali 18,709 18.0 … … 3 9 … … …Mauritania 11,066 26.8 … … 10 … 728 47 7,622Mauritius 2,028 98.0 … … 59 150 … … …Mayotte … … … … … … … … …Morocco 57,799 62.0 … 1,212 37 71 1,989 3,836 4,959Mozambique 30,400 18.7 … … 4 10 3,116 114 695Namibia 42,237 12.8 47 591 71 109 … … …Niger 18,951 20.7 … … 6 5 … … …Nigeria 193,200 15.0 … … 30 31 3,528 174 77Réunion … … … … … … … … …Rwanda 14,008 19.0 … … 2 4 … … …Saint Helena … … … … … … … … …São Tomé and Príncipe … … … … … … … … …Senegal 13,576 29.3 … … 11 20 … 129 384Seychelles … … … … … … … … …Sierra Leone 11,300 8.0 … … 10 5 … … …Somalia 22,100 11.8 … … 2 … … … …South Africa 362,099 17.3 … 434 139 159 24,487 13,865 106,014Sudan 11,900 36.3 … … 9 28 4,578 34 766Swaziland 3,594 30.0 … … 66 89 300 0 2Togo 7,520 31.6 … … 24 2 … … …Tunisia 19,232 65.8 … 16,611 48 103 2,218 1,487 2,197Uganda 70,746 23.0 … … 2 7 … … …United Republic of Tanzania 78,891 8.6 … … 5 12 2,6002 4752 7282

Western Sahara … … … … … … … … …Zambia 66,781 22.0 … … 14 18 … … …Zimbabwe 97,267 19.0 … … 32 106 2,583 … 1,580ASIAAfghanistan 42,150 29.3 … … … 23 … … …Armenia 7,515 89.8 2,693 434 5 105 845 27 354Azerbaijan 59,141 49.4 11,786 8,222 52 61 2,099 1,047 10,021Bahrain … … … … … … … … …Bangladesh 239,226 9.5 … … 1 2 2,835 5,609 870Bhutan … … … … … … … … …Brunei Darussalam … … … … … … … … …Cambodia 38,257 6.3 201 3 1 … … … …China 3,583,715 70.7 1,150,677 975,420 5 32 60,809 772,834 2,511,804China, Hong Kong SAR 2,009 100.0 … … 66 72 … … …China, Macao SAR … … … … … … … … …Cyprus … … … … … … … … …Democratic People's Republic of Korea 25,554 2.8 … … … … … … …Georgia 20,329 38.6 5,269 586 107 116 1,513 774 6,928India 3,316,452 47.4 … … 4 12 63,327 769,956 521,371Indonesia 391,009 55.4 … … 16 76 3,370 14,344 4,390Iran (Islamic Republic of) 172,927 72.8 … … 34 16 7,335 13,900 21,829Iraq 45,550 84.3 … … 14 … 2,032 61 640


TABLE B.6continued



2000–20071 2000–20071 2000–20071 2000–20071 1990 2007 2000–20081 2000–20081 2000–20081

Israel 17,870 100.0 … … 210 305 1,005 1,968 1,055Japan 1,196,999 79.3 947,562 327,632 469 595 20,048 255,865 23,032Jordan 7,768 100.0 … … 60 137 251 … 789Kazakhstan 93,123 90.3 103,381 53,816 76 170 14,205 14,450 214,907Kuwait 5,749 85.0 … … … 502 … … …Kyrgyzstan 34,000 91.1 6,468 819 44 59 417 60 849Lao People's Democratic Republic 29,811 13.4 … … 9 21 … … …Lebanon 6,970 … … … 321 … … … …Malaysia 93,109 79.8 … … 124 272 1,665 2,268 1,350Maldives … … … … … … … … …Mongolia 49,250 3.5 557 242 21 61 1,810 1,400 8,261Myanmar 27,000 11.9 … … 2 7 … 4,163 885Nepal 17,280 56.9 … … … 5 … … …Occupied Palestinian Territory 5,147 100 … … … 16 … … …Oman 48,874 41.3 … … 130 225 … … …Pakistan 260,420 65.4 263,788 129,249 6 11 7,791 24,731 6,187Philippines 200,037 9.9 … … 10 32 479 83 …Qatar 7,790 90.0 … … … 724 … … …Republic of Korea 102,061 77.6 97,854 12,545 79 338 3,381 32,025 11,566Saudi Arabia 221,372 21.5 … … 165 … 2,758 337 1,748Singapore 3,297 100.0 … … 130 149 … … …Sri Lanka 97,286 81.0 21,067 … 21 58 1,463 4,767 135Syrian Arab Republic 40,032 100.0 589 … 26 52 2,139 1,120 2,370Tajikistan 27,767 … 150 14,572 3 38 616 53 1,274Thailand 180,053 98.5 … … 46 … 4,429 8,037 3,161Timor-Leste … … … … … … … … …Turkey 426,951 … 209,115 177,399 50 131 8,699 5,097 10,104Turkmenistan 24,000 81.2 … … … 106 3,181 1,570 10,973United Arab Emirates 4,030 100.0 … … 121 313 … … …Uzbekistan 81,600 87.3 … 1,200 … … 4,230 2,264 21,594Viet Nam 160,089 47.6 49,372 20,537 … 13 3,147 4,659 3,910Yemen 71,300 8.7 … … 34 35 … … …EUROPEAlbania 18,000 39.0 197 2,200 11 102 423 51 53Andorra … … … … … … … … …Austria 107,206 100.0 69,000 26,411 421 556 5,755 10,275 18,710Belarus 94,797 88.6 9,353 15,779 61 282 5,491 8,188 47,933Belgium 153,070 78.2 130,868 51,572 423 539 3,513 10,403 7,882Bosnia and Herzegovina 21,846 52.3 … 300 114 170 1,016 78 1,237Bulgaria 40,231 98.4 13,688 11,843 163 295 4,159 2,335 4,673Channel Islands … … … … … … … … …Croatia 29,038 89.1 3,277 10,175 … 377 2,722 1,810 3,312Czech Republic 128,511 100.0 90,055 46,600 246 470 9,487 6,759 15,961Denmark 72,412 100.0 70,635 11,495 368 466 2,133 5,843 …Estonia 58,034 28.8 3,190 7,641 211 444 816 274 5,683Faeroe Islands … … … … … … … … …Finland 78,889 65.4 71,300 26,400 441 559 5,919 4,052 10,777France 951,125 100.0 775,000 313,000 494 600 29,901 88,283 41,530Germany 644,471 100.0 966,692 461,900 405 623 33,862 76,997 91,178Gibraltar … … … … … … … … …Greece 117,533 91.8 … 18,360 248 …4 2,552 2,003 786Holy See … … … … … … … … …Hungary 195,719 37.7 11,784 30,495 212 384 7,942 5,927 7,786Iceland … … … … … … … … …Ireland 96,602 100.0 … 15,900 270 537 1,919 1,976 103Isle of Man … … … … … … … … …Italy 487,700 100.0 97,560 192,700 529 677 16,862 46,998 19,918Latvia 69,687 100.0 2,664 2,729 135 459 2,263 951 17,704Liechtenstein … … … … … … … … …Lithuania 80,715 28.6 42,739 18,134 160 479 1,765 398 14,748Luxembourg … … … … … … … … …Malta … … … … … … … … …Moldova 12,755 85.7 1,640 1,577 53 120 1,156 485 3,092Monaco … … … … … … … … …Montenegro … … … … … … … … …Netherlands 126,100 90.0 … 77,100 405 503 2,896 15,313 …Norway 92,920 79.6 60,597 14,966 458 572 4,114 2,705 …Poland 258,910 90.3 27,359 136,490 168 451 19,627 17,958 39,200Portugal 82,900 86.0 … 45,032 222 507 2,842 3,814 2,550Romania 198,817 30.2 7,985 51,531 72 180 10,784 6,880 12,861Russian Federation 933,000 80.9 78,000 199,000 87 245 84,158 175,800 2,400,000San Marino … … … … … … … … …Serbia 39,184 62.7 3,865 452 137 244 4,058 749 4,214Slovakia 43,761 87.0 7,816 22,114 194 282 3,592 2,279 9,004Slovenia 38,708 100.0 817 12,112 306 547 1,228 834 3,520Spain 666,292 99.0 397,117 132,868 360 601 15,046 23,344 10,224Sweden 427,045 31.7 109,300 40,123 464 523 9,830 7,156 11,500

221Data Tables

TABLE B.6continued



2000–20071 2000–20071 2000–20071 2000–20071 1990 2007 2000–20081 2000–20081 2000–20081

Switzerland 71,354 100.0 94,250 16,337 491 569 3,499 18,367 16,227TFYR Macedonia3 13,840 … 1,027 8,299 132 136 699 148 743Ukraine 169,422 97.8 55,446 26,625 63 140 21,676 53,056 257,006United Kingdom 420,009 100.0 736,000 166,728 400 527 16,321 51,759 12,512LATIN AMERICA AND THE CARIBBEANAnguilla … … … … … … … … …Antigua and Barbuda … … … … … … … … …Argentina 231,374 30.0 … … 181 314 35,753 … 12,871Aruba … … … … … … … … …Bahamas … … … … … … … … …Barbados … … … … … … … … …Belize … … … … … … … … …Bolivia 62,479 7.0 … … 41 68 2,866 313 1,060Brazil 1,751,868 5.5 … … 88 198 29,817 … 267,700British Virgin Islands … … … … … … … … …Cayman Islands … … … … … … … … …Chile 79,814 20.2 … … 81 164 5,898 759 4,296Colombia 164,278 … 157 39,726 39 66 1,663 … 9,049Costa Rica 36,654 25.5 27 … 87 152 … … …Cuba 60,856 49.0 5,266 2,133 37 38 5,076 1,285 1,351Dominica … … … … … … … … …Dominican Republic 12,600 49.4 … … 75 123 … … …Ecuador 43,670 14.8 11,819 5,453 35 63 … … …El Salvador 10,029 19.8 … … 33 84 … … …Falkland Islands (Malvinas) … … … … … … … … …French Guiana … … … … … … … … …Grenada … … … … … … … … …Guadeloupe … … … … … … … … …Guatemala 14,095 34.5 … … 21 117 … … …Guyana … … … … … … … … …Haiti 4,160 24.3 … … 8 … … … …Honduras 13,600 20.4 … … 22 97 … … …Jamaica 22,121 73.3 … … 52 188 … … …Martinique … … … … … … … … …Mexico 360,075 38.2 449,917 209,392 119 244 26,677 84 71,136Montserrat … … … … … … … … …Netherlands Antilles … … … … … … … … …Nicaragua 18,669 11.4 … … 19 48 … … …Panama 11,643 34.6 … … 75 188 … … …Paraguay 29,500 50.8 … … 27 82 … … …Peru 78,986 13.9 … … … 52 2,020 55 627Puerto Rico 25,645 95.0 … 10 295 642 … … …Saint Kitts and Nevis … … … … … … … … …Saint Lucia … … … … … … … … …Saint Vincent and the Grenadines … … … … … … … … …Suriname … … … … … … … … …Trinidad and Tobago 8,320 51.1 … … 117 351 … … …Turks and Caicos Islands … … … … … … … … …United States Virgin Islands … … … … … … … … …Uruguay 77,732 10.0 2,032 … 138 176 2,993 15 284Venezuela (Bolivarian Republic of) 96,155 33.6 … … 93 147 336 … 81NORTHERN AMERICABermuda … … … … … … … … …Canada 1,409,000 39.9 493,814 184,774 605 597 57,216 3,056 358,154Greenland … … … … … … … … …Saint-Pierre-et-Miquelon … … … … … … … … …United States of America 6,544,257 65.3 7,940,003 1,889,923 758 8145 227,058 9,935 2,788,2306

OCEANIAAmerican Samoa … … … … … … … … …Australia 815,074 … 301,550 173,000 530 653 9,661 1,526 61,019Cook Islands … … … … … … … … …Fiji … … … … … … … … …French Polynesia … … … … … … … … …Guam … … … … … … … … …Kiribati … … … … … … … … …Marshall Islands … … … … … … … … …Micronesia (Federated States of) … … … … … … … … …Nauru … … … … … … … … …New Caledonia … … … … … … … … …New Zealand 93,748 65.4 … … 524 729 … …Niue … … … … … … … … …Northern Mariana Islands … … … … … … … … …Palau … … … … … … … … …Papua New Guinea 19,600 3.5 … … 27 9 … … …Pitcairn … … … … … … … … …Samoa … … … … … … … … …


TABLE B.6continued



2000–20071 2000–20071 2000–20071 2000–20071 1990 2007 2000–20081 2000–20081 2000–20081

Solomon Islands … … … … … … … … …Tokelau … … … … … … … … …Tonga … … … … … … … … …Tuvalu … … … … … … … … …Vanuatu … … … … … … … … …Wallis and Futuna Islands … … … … … … … … …

Sources: World Bank (2005) World Development Indicators 2005, World Bank, Washington, DC.; World Bank (2010) World Development Indicators 2010, World Bank, Washington, DC.

Notes:(1) Data are for the latest year available in the period shown. (2) Includes Tazara railway.(3) The former Yugoslav Republic of Macedonia.(4) The number of passenger cars per 1,000 people is 429. Passenger cars as a subset of motor vehicles, are road motor vehicles other than two-wheelers, intended for the carriage of passengers and designed to seat no morethan nine peole (including the driver).(5) Data are from the US Federal Highway Adminstration.(6) Refers to class 1 railways only.

223Data Tables

TABLE B.7Greenhouse Gas Emissions and Rate of Change

Carbon dioxide Methane Nitrous oxide Other greenhouse Total greenhouseemissions emissions emissions gas emissions gas emissions

’000 % ’000 tonnes From non- % ’000 tonnes From non- % ’000 tonnes % ’000 tonnes % tonnes change of CO2 agricultural change of CO2 agricultural change of CO2 change of CO2 change

equivalent sources % equivalent sources % equivalent equivalent2005 1990–2005 2005 2005 1990–2005 2005 2005 1990–2005 2005 1990–2005 2005 1990–2005

AFRICAAlgeria 138,078 5.0 24,310 84.7 2.1 10,330 10.9 1.2 110 -3.5 172,828 4.2Angola 9,849 8.2 37,020 60.9 11.4 28,350 64.1 30.3 0 … 75,219 …Benin 2,565 17.3 4,840 52.5 5.2 4,660 32.0 8.0 0 … 12,065 …Botswana 4,521 7.2 4,480 28.1 223.1 2,460 3.7 … 0 … 11,461 …Burkina Faso 788 2.3 … … … … … … … … … …Burundi 169 -3.0 … … … … … … … … … …Cameroon 3,715 7.6 15,110 44.0 2.9 14,540 15.0 5.0 890 0.7 34,255 4.0Cape Verde 297 15.8 … … … … … … … … … …Central African Republic 234 1.2 … … … … … … … … … …Chad 392 11.2 … … … … … … … … … …Comoros 88 1.0 … … … … … … … … … …Congo 1,605 2.3 50,320 73.7 5.4 38,680 76.8 6.6 0 … 90,605 …Côte d'Ivoire 8,160 2.7 15,320 79.4 12.2 12,350 75.0 26.8 0 … 35,830 …Democratic Republic of the Congo 2,143 -3.2 5,750 88.2 7.7 2,250 84.4 11.6 0 … 10,143 …Djibouti 473 1.2 … … … … … … … … … …Egypt 173,355 8.6 32,960 55.8 2.8 27,810 14.4 4.3 1,820 -1.3 235,945 6.6Equatorial Guinea 4,338 232.5 … … … … … … … … … …Eritrea 751 … 2,410 22.4 1.0 2,350 0.9 5.0 0 … 5,511 …Ethiopia 5,485 5.5 47,740 22.8 1.5 63,130 1.4 1.6 0 … 116,355 …Gabon 1,869 -4.6 2,040 95.6 -2.3 420 42.9 -5.2 0 … 4,329 …Gambia 319 4.5 … … … … … … … … … …Ghana 7,467 6.0 8,630 50.4 4.2 10,520 11.4 8.8 170 -0.7 26,787 6.1Guinea 1,359 1.9 … … … … … … … … … …Guinea-Bissau 271 0.5 … … … … … … … … … …Kenya 10,944 5.9 20,310 35.0 0.3 19,060 3.6 -0.8 0 … 50,314 …Lesotho … … … … … … … … … … … …Liberia 736 3.5 … … … … … … … … … …Libyan Arab Jamahiriya 54,854 2.4 8,540 91.1 -0.2 2,050 8.3 -1.9 290 12.7 65,734 1.8Madagascar 2,796 12.2 … … … … … … … … … …Malawi 1,048 4.8 … … … … … … … … … …Mali 568 2.3 … … … … … … … … … …Mauritania 1,649 -2.5 … … … … … … … … … …Mauritius 3,408 8.9 … … … … … … … … … …Mayotte … … … … … … … … … … … …Morocco 47,496 6.8 13,240 58.4 3.1 15,510 24.8 0.5 0 … 76,246 …Mozambique 1,854 5.7 11,680 35.7 1.6 9,930 0.3 15.8 0 … 23,464 …Namibia 2,722 2470.0 4,260 10.1 -0.1 4,620 0.9 0.6 0 … 11,602 …Niger 927 -0.8 … … … … … … … … … …Nigeria 113,786 10.1 78,290 66.3 2.1 39,030 12.9 2.6 80 -2.2 231,186 4.9Réunion … … … … … … … … … … … …Rwanda 766 0.8 … … … … … … … … … …Saint Helena … … … … … … … … … … … …São Tomé and Príncipe 103 3.7 … … … … … … … … … …Senegal 5,573 5.0 6,340 24.1 0.9 10,250 1.0 4.3 10 … 22,173 …Seychelles 696 34.2 … … … … … … … … … …Sierra Leone 1,004 10.6 … … … … … … … … … …Somalia 253 85.3 … … … … … … … … … …South Africa 408,792 1.5 59,200 76.2 0.9 29,250 17.3 0.7 2,600 5.3 499,842 1.4Sudan 10,992 6.5 67,310 26.7 4.6 59,750 3.8 3.4 0 … 138,052 …Swaziland 1,019 9.3 … … … … … … … … … …Togo 1,337 4.9 2,840 51.4 3.9 5,470 11.2 11.7 0 … 9,647 …Tunisia 22,783 4.8 4,390 65.8 1.2 7,230 5.8 4.6 30 … 34,433 …Uganda 2,338 12.4 … … … … … … … … … …United Republic of Tanzania 5,082 7.6 39,460 36.5 3.1 31,690 15.7 2.4 0 … 76,232 …Western Sahara … … … … … … … … … … … …Zambia 2,363 -0.2 16,770 31.4 4.7 11,410 34.9 9.2 0 … 30,543 …Zimbabwe 11,542 -2.0 10,400 39.6 -0.3 10,160 2.9 0.9 20 … 32,122 …ASIAAfghanistan 700 -4.9 … … … … … … … … … …Armenia 4,346 … 2,300 49.1 -1.7 450 6.7 -3.4 10 … 7,106 …Azerbaijan 35,259 … 11,550 54.6 -1.4 4,040 6.4 0.0 50 -4.8 50,899 …Bahrain 19,668 4.4 1,970 99.5 1.6 60 66.7 1.3 190 -6.0 21,888 2.8Bangladesh 40,080 10.6 92,530 30.8 0.9 37,100 8.1 4.4 0 … 169,710 …Bhutan 392 13.7 … … … … … … … … … …Brunei Darussalam 5,903 -0.5 2,060 99.0 1.7 370 97.3 28.6 0 … 8,333 …Cambodia 3,719 48.3 14,890 28.5 … 3,820 25.9 0.0 0 … 22,429 …China 5,621,470 8.9 995,760 50.0 0.7 566,680 7.3 1.6 119,720 85.7 7,303,630 6.2China, Hong Kong SAR 41,062 3.2 1,090 99.1 -0.5 200 95.0 -0.3 330 … 42,682 …China, Macao SAR 2,308 8.2 … … … … … … … … … …Cyprus 7,497 4.1 330 48.5 1.5 640 9.4 1.2 0 … 8,467 …Democratic People's Republic of Korea 83,411 -4.4 10,650 63.6 0.6 23,160 2.5 10.1 860 12.4 118,081 -3.7Georgia 4,796 … 4,330 48.3 -1.7 3,390 50.7 0.0 10 … 12,526 …India 1,422,808 7.1 712,330 35.2 0.9 300,680 7.0 2.2 9,510 1.2 2,445,328 3.9Indonesia 330,537 8.0 224,330 58.8 1.6 69,910 27.4 1.1 900 -2.3 625,677 4.0Iran (Islamic Republic of) 435,719 6.1 95,060 78.2 4.9 66,140 2.4 2.4 1,560 -1.8 598,479 5.3


TABLE B.7continued




Iraq 88,566 4.6 10,980 85.3 -0.1 3,990 7.0 -2.6 470 1.4 104,006 3.2Israel 63,618 6.0 1,170 63.2 1.1 1,820 16.5 -0.3 1,140 2.4 67,748 5.5Japan 1,299,243 0.7 53,480 86.6 -0.5 23,590 50.7 -1.7 70,570 11.0 1,446,883 0.8Jordan 21,317 7.0 1,610 75.8 3.3 1,240 6.5 0.5 10 … 24,177 …Kazakhstan 177,110 … 28,270 62.1 -3.3 5,530 9.8 -5.1 0 … 210,910 …Kuwait 89,805 8.0 11,200 98.5 4.3 540 18.5 7.7 390 3.7 101,935 7.5Kyrgyzstan 5,566 … 3,520 27.8 -1.7 3,260 1.2 -1.5 60 … 12,406 …Lao People's Democratic Republic 1,407 33.3 … … … … … … … … … …Lebanon 17,481 6.2 980 81.6 2.3 1,020 6.9 2.5 0 … 19,481 …Malaysia 183,171 14.9 25,510 77.7 1.3 9,920 35.7 -1.0 530 -3.0 219,131 9.5Maldives 678 22.7 … … … … … … … … … …Mongolia 8,805 -0.8 4,840 16.1 -2.3 22,850 0.4 8.6 0 … 36,495 …Myanmar 10,464 9.7 60,840 30.0 3.4 25,900 33.2 5.3 10 … 97,214 …Nepal 3,166 26.6 36,040 19.5 0.4 7,100 11.5 1.6 0 … 46,306 …Occupied Palestinian Territory 2,752 … … … … … … … … … … …Oman 31,444 13.6 4,260 87.1 7.4 1,140 3.5 2.1 0 … 36,844 …Pakistan 133,960 6.4 110,300 33.7 2.2 80,040 3.6 3.0 620 -0.8 324,920 3.8Philippines 76,369 4.8 44,860 33.3 1.0 18,940 4.4 0.4 350 16.7 140,519 2.6Qatar 46,676 19.8 5,190 98.5 8.8 280 14.3 3.7 0 … 52,146 …Republic of Korea 473,836 6.4 31,280 68.9 0.9 22,020 63.9 8.8 8,700 4.1 535,836 5.9Saudi Arabia 366,766 4.7 63,500 98.1 4.0 7,720 7.9 -0.4 1,530 -2.2 439,516 4.4Singapore 59,514 1.8 1,260 95.2 4.7 7,970 99.2 288.5 1,300 15.0 70,044 3.0Sri Lanka 11,582 13.8 10,280 38.2 0.0 3,130 10.9 2.0 0 … 24,992 …Syrian Arab Republic 66,549 5.2 7,960 65.3 2.5 9,430 5.1 1.3 0 … 83,939 …Tajikistan 5,800 … 3,270 31.5 -0.8 1,590 0.6 -3.3 120 3.3 10,780 …Thailand 270,894 12.2 78,840 23.9 1.0 27,990 12.1 2.1 940 -2.7 378,664 6.8Timor-Leste 176 … … … … … … … … … … …Turkey 248,295 4.6 23,140 40.5 -1.0 47,950 12.0 0.6 1,480 -3.2 320,865 3.0Turkmenistan 41,726 … 23,060 84.8 -2.0 3,200 21.3 -1.5 250 … 68,236 …United Arab Emirates 135,594 9.8 34,250 98.3 5.3 2,730 9.5 12.9 480 7.9 173,054 8.7Uzbekistan 112,481 … 51,480 76.8 1.6 14,660 1.7 0.2 760 … 179,381 …Viet Nam 101,764 25.0 75,080 33.2 2.8 37,470 5.1 11.3 10 … 214,324 …Yemen 20,159 … 9,040 72.3 6.4 7,080 1.1 2.6 10 … 36,289 …EUROPEAlbania 4,532 -2.6 2,170 30.0 -0.2 1,390 2.9 -2.7 50 … 8,142 …Andorra … … … … … … … … … … … …Austria 72,767 1.3 7,210 49.9 -0.8 4,620 14.7 -1.3 3,310 11.6 87,907 1.1Belarus 64,289 … 16,620 61.2 -0.9 10,360 34.4 -2.1 440 … 91,709 …Belgium 109,312 0.1 7,610 40.3 -1.7 9,650 34.6 -0.9 9,380 474.4 135,952 0.4Bosnia and Herzegovina 25,593 … 2,850 67.4 2.8 1,020 17.6 -0.7 850 5.7 30,313 …Bulgaria 46,958 -2.6 6,140 67.3 -2.4 5,880 35.5 -3.7 650 … 59,628 …Channel Islands … … … … … … … … … … … …Croatia 23,600 … 3,690 70.2 -0.4 3,590 36.2 0.4 720 0.5 31,600 …Czech Republic 114,636 … 14,930 82.8 -2.2 6,570 25.0 -2.6 3,530 1170.0 139,666 …Denmark 46,793 -0.5 4,920 32.3 -0.9 7,380 21.4 -1.7 1,460 30.8 60,553 -0.6Estonia 18,203 … 1,230 65.0 -3.5 610 16.4 -4.2 60 … 20,103 …Faeroe Islands 678 0.6 … … … … … … … … … …Finland 54,755 0.5 5,470 69.7 -1.7 5,330 40.5 -0.8 1,030 24.5 66,585 0.2France 394,360 -0.1 43,520 28.9 -1.6 78,090 22.7 -0.8 27,010 10.1 542,980 -0.1Germany 803,065 … 58,100 60.8 -3.1 69,470 25.8 -0.7 41,980 18.3 972,615 …Gibraltar … … … … … … … … … … … …Greece 98,847 2.4 7,410 60.9 1.1 13,090 8.7 0.0 1,620 7.0 120,967 2.0Holy See … … … … … … … … … … … …Hungary 58,778 -0.3 11,050 81.7 -1.5 8,760 24.0 -1.8 1,540 6.8 80,128 -0.7Iceland 2,184 0.4 330 45.5 -0.4 650 40.0 3.7 80 -6.0 3,244 -0.7Ireland 44,001 2.8 3,660 68.0 -4.6 12,320 7.4 -0.3 2,050 117.6 62,031 0.8Isle of Man … … … … … … … … … … … …Italy 469,798 0.7 36,670 62.3 -0.9 37,200 29.5 0.3 27,710 32.1 571,378 0.8Latvia 7,057 … 2,290 70.7 -3.1 1,390 11.5 -3.2 110 … 10,847 …Liechtenstein … … … … … … … … … … … …Lithuania 13,989 … 3,650 61.9 -3.5 2,860 9.8 -2.1 150 … 20,649 …Luxembourg 11,318 1.0 180 100.0 -1.7 80 100.0 4.0 50 … 11,628 …Malta 2,587 1.0 100 60.0 0.7 50 20.0 0.0 0 … 2,737 …Moldova 8,138 … 2,590 69.1 -3.1 970 5.2 -4.7 360 … 12,058 …Monaco … … … … … … … … … … … …Montenegro … … … … … … … … … … … …Netherlands 174,890 0.3 15,180 50.8 -1.4 16,800 48.5 -0.9 5,300 -0.7 212,170 0.0Norway 60,811 6.3 12,080 85.7 3.9 4,680 47.0 -0.8 1,770 -4.3 79,341 4.1Poland 303,346 -0.8 60,060 81.6 -2.2 26,110 27.5 -1.2 1,270 11.7 390,786 -1.1Portugal 65,413 3.2 7,140 47.1 -0.3 7,000 19.3 0.1 1,050 47.2 80,603 2.5Romania 91,791 -2.8 23,260 69.9 -3.0 11,790 30.4 -3.5 2,220 3.2 129,061 -2.9Russian Federation 1,514,412 … 501,380 92.1 -1.4 42,650 23.8 -4.5 56,600 12.8 2,115,042 …San Marino … … … … … … … … … … … …Serbia … … … … … … … … … … … …Slovakia 37,666 … 5,290 80.5 -1.9 2,760 42.0 -2.7 710 466.7 46,426 …

225Data Tables

TABLE B.7continued




Slovenia 14,916 … 1,630 52.1 -0.4 1,100 11.8 0.2 210 -4.3 17,856 …Spain 356,196 3.7 38,010 55.9 1.3 48,520 14.3 2.5 15,050 15.9 457,776 3.5Sweden 51,454 0.0 6,460 58.5 -1.1 6,070 23.2 -0.3 1,620 4.2 65,604 -0.1Switzerland 41,323 -0.3 4,150 32.0 -0.9 2,840 21.8 -0.7 3,310 22.4 51,623 0.0TFYR Macedonia1 11,230 … … … … … … … … … … …Ukraine 326,997 … 75,640 84.3 -3.2 23,270 45.8 -4.4 1,390 147.8 427,297 …United Kingdom 553,238 -0.2 39,400 49.3 -2.8 65,480 47.8 -0.3 14,030 9.2 672,148 -0.4LATIN AMERICA AND THE CARIBBEANAnguilla … … … … … … … … … … … …Antigua and Barbuda 410 2.4 … … … … … … … … … …Argentina 158,823 2.7 94,340 36.1 1.0 83,410 2.3 1.9 930 -3.4 337,503 1.9Aruba 2,308 1.7 … … … … … … … … … …Bahamas 2,107 0.5 … … … … … … … … … …Barbados 1,315 1.5 … … … … … … … … … …Belize 817 10.8 … … … … … … … … … …Bolivia 9,559 4.9 27,120 65.5 5.0 28,300 56.7 6.5 0 … 64,979 …Brazil 349,696 4.5 421,820 32.9 3.2 300,300 25.6 2.1 7,760 3.1 1,079,576 3.2British Virgin Islands … … … … … … … … … … … …Cayman Islands 502 6.6 … … … … … … … … … …Chile 59,397 4.5 19,560 70.1 2.5 12,590 11.3 3.6 10 … 91,557 …Colombia 59,130 0.2 61,690 44.9 1.7 24,530 22.0 1.1 330 4.9 145,680 0.9Costa Rica 7,273 9.8 2,450 42.0 -2.3 2,850 1.1 -1.1 0 … 12,573 …Cuba 24,853 -1.7 9,490 37.6 -0.3 8,330 12.6 -2.6 110 … 42,783 …Dominica 114 6.3 … … … … … … … … … …Dominican Republic 19,877 7.2 5,960 37.9 0.9 2,850 3.9 -2.1 0 … 28,687 …Ecuador 30,646 5.5 12,890 42.6 0.4 8,500 2.4 -0.3 0 … 52,036 …El Salvador 6,287 9.4 3,200 51.9 1.1 2,250 4.9 0.7 0 … 11,737 …Falkland Islands (Malvinas) … … … … … … … … … … … …French Guiana … … … … … … … … … … … …Grenada 234 6.3 … … … … … … … … … …Guadeloupe … … … … … … … … … … … …Guatemala 11,860 8.9 8,990 57.3 3.5 7,980 29.2 4.5 0 … 28,830 …Guyana 1,491 2.1 … … … … … … … … … …Haiti 1,766 5.2 3,740 38.8 2.0 4,290 1.6 4.9 0 … 9,796 …Honduras 7,779 13.4 5,380 28.1 0.5 3,860 2.1 0.6 0 … 17,019 …Jamaica 10,157 1.8 1,160 52.6 -0.3 1,020 3.9 -1.1 0 … 12,337 …Martinique … … … … … … … … … … … …Mexico 429,065 0.8 120,100 60.4 1.7 75,500 9.9 0.5 3,160 4.2 627,825 0.9Montserrat … … … … … … … … … … … …Netherlands Antilles 3,752 -2.6 110 90.9 1.5 60 66.7 6.7 0 … 3,922 …Nicaragua 4,151 3.8 6,350 19.8 2.4 3,210 3.1 -1.0 0 … 13,711 …Panama 5,976 6.1 3,040 27.6 0.2 2,070 4.3 -1.2 0 … 11,086 …Paraguay 3,829 4.6 17,750 29.1 3.5 12,870 18.2 1.9 0 … 34,449 …Peru 37,135 5.0 21,510 51.9 1.6 18,720 10.6 2.1 80 … 77,445 …Puerto Rico … … … … … … … … … … … …Saint Kitts and Nevis 136 7.0 … … … … … … … … … …Saint Lucia 374 8.4 … … … … … … … … … …Saint Vincent and the Grenadines 194 9.4 … … … … … … … … … …Suriname 2,378 2.1 … … … … … … … … … …Trinidad and Tobago 30,931 5.5 3,820 99.0 3.5 360 8.3 0.4 0 … 35,111 …Turks and Caicos Islands … … … … … … … … … … … …United States Virgin Islands … … … … … … … … … … … …Uruguay 5,987 3.3 17,700 9.7 1.7 15,630 0.4 0.2 20 … 39,337 …Venezuela (Bolivarian Republic of) 152,419 1.7 65,730 66.4 3.9 26,460 22.2 1.5 2,300 4.9 246,909 2.2NORTHERN AMERICABermuda 564 -0.4 … … … … … … … … … …Canada 559,376 1.6 103,830 77.8 1.7 51,390 13.3 0.1 11,010 -0.9 725,606 1.4Greenland 557 0.0 … … … … … … … … … …Saint-Pierre-et-Miquelon … … … … … … … … … … … …United States of America 5,837,067 1.3 810,280 81.6 -0.4 456,210 25.3 0.7 108,420 1.3 7,211,977 1.1OCEANIAAmerican Samoa … … … … … … … … … … … …Australia 365,524 1.7 116,840 38.5 0.8 114,500 5.1 0.5 4,580 5.0 601,444 1.3Cook Islands … … … … … … … … … … … …Fiji 1,663 6.9 … … … … … … … … … …French Polynesia 854 2.4 … … … … … … … … … …Guam … … … … … … … … … … … …Kiribati 26 1.1 … … … … … … … … … …Marshall Islands 84 5.1 … … … … … … … … … …Micronesia (Federated States of) … … … … … … … … … … … …Nauru … … … … … … … … … … … …New Caledonia 2,799 4.8 … … … … … … … … … …New Zealand 30,081 2.2 27,490 17.7 0.0 27,960 0.6 -1.2 820 7.0 86,351 0.2Niue … … … … … … … … … … … …Northern Mariana Islands … … … … … … … … … … … …


TABLE B.7continued




Palau 117 … … … … … … … … … … …Papua New Guinea 4,609 7.7 … … … … … … … … … …Pitcairn … … … … … … … … … … … …Samoa 158 1.8 … … … … … … … … … …Solomon Islands 180 0.8 … … … … … … … … … …Tokelau … … … … … … … … … … … …Tonga 132 4.8 … … … … … … … … … …Tuvalu … … … … … … … … … … … …Vanuatu 88 1.8 … … … … … … … … … …Wallis and Futuna Islands … … … … … … … … … … … …

Source: World Bank (2010). Data retrieved 17 June 2010 from World Development Indicators Online (WDI) database.

Notes:(1) The former Yugoslav Republic of Macedonia.

227Data Tables

TABLE B.8Greenhouse Gas Emissions per Capita and as Proportion of World Total

Greenhouse gas emissions per capita Greenhouse gas emissions asmetric tonnes of CO2 equivalent percetage of world total

Carbon dioxide Methane Nitrous oxide Other Total Carbon dioxide1 Methane2 Nitrous oxide3 Other4 Total5

2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

AFRICAAlgeria 4.20 0.74 0.31 0.00 5.25 0.50 0.37 0.27 0.02 0.45Angola 0.59 2.23 1.71 0.00 4.53 0.04 0.56 0.75 0.00 0.19Benin 0.33 0.62 0.59 0.00 1.54 0.01 0.07 0.12 0.00 0.03Botswana 2.46 2.44 1.34 0.00 6.24 0.02 0.07 0.06 0.00 0.03Burkina Faso 0.06 … … … … 0.00 … … … …Burundi 0.02 … … … … 0.00 … … … …Cameroon 0.21 0.85 0.82 0.05 1.93 0.01 0.23 0.38 0.15 0.09Cape Verde 0.62 … … … … 0.00 … … … …Central African Republic 0.06 … … … … 0.00 … … … …Chad 0.04 … … … … 0.00 … … … …Comoros 0.15 … … … … 0.00 … … … …Congo 0.04 0.10 0.04 0.00 0.18 0.01 0.09 0.06 0.00 0.03Côte d'Ivoire 0.42 0.80 0.64 0.00 1.86 0.03 0.23 0.33 0.00 0.09Democratic Republic of the Congo 0.47 14.73 11.32 0.00 26.52 0.01 0.76 1.02 0.00 0.23Djibouti 0.59 … … … … 0.00 … … … …Egypt 2.25 0.43 0.36 0.02 3.06 0.63 0.50 0.73 0.30 0.61Equatorial Guinea 7.13 … … … … 0.02 … … … …Eritrea 0.17 0.54 0.53 0.00 1.24 0.00 0.04 0.06 0.00 0.01Ethiopia 0.07 0.64 0.85 0.00 1.56 0.02 0.72 1.67 0.00 0.30Gabon 1.37 1.49 0.31 0.00 3.17 0.01 0.03 0.01 0.00 0.01Gambia 0.21 … … … … 0.00 … … … …Ghana 0.34 0.39 0.48 0.01 1.22 0.03 0.13 0.28 0.03 0.07Guinea 0.15 … … … … 0.00 … … … …Guinea-Bissau 0.18 … … … … 0.00 … … … …Kenya 0.31 0.57 0.53 0.00 1.41 0.04 0.31 0.50 0.00 0.13Lesotho … … … … … … … … … …Liberia 0.22 … … … … 0.00 … … … …Libyan Arab Jamahiriya 9.26 1.44 0.35 0.05 11.10 0.20 0.13 0.05 0.05 0.17Madagascar 0.16 … … … … 0.01 … … … …Malawi 0.08 … … … … 0.00 … … … …Mali 0.05 … … … … 0.00 … … … …Mauritania 0.55 … … … … 0.01 … … … …Mauritius 2.74 … … … … 0.01 … … … …Mayotte … … … … … … … … … …Morocco 1.56 0.43 0.51 0.00 2.50 0.17 0.20 0.41 0.00 0.20Mozambique 0.09 0.56 0.48 0.00 1.13 0.01 0.18 0.26 0.00 0.06Namibia 1.35 2.12 2.30 0.00 5.77 0.01 0.06 0.12 0.00 0.03Niger 0.07 … … … … 0.00 … … … …Nigeria 0.81 0.56 0.28 0.00 1.65 0.41 1.19 1.03 0.01 0.60Réunion … … … … … … … … … …Rwanda 0.09 … … … … 0.00 … … … …Saint Helena … … … … … … … … … …São Tomé and Príncipe 0.67 … … … … 0.00 … … … …Senegal 0.49 0.56 0.91 0.00 1.96 0.02 0.10 0.27 0.00 0.06Seychelles 8.40 … … … … 0.00 … … … …Sierra Leone 0.20 … … … … 0.00 … … … …Somalia 0.03 … … … … 0.00 … … … …South Africa 8.72 1.26 0.62 0.06 10.66 1.48 0.90 0.77 0.44 1.29Sudan 0.28 1.74 1.54 0.00 3.56 0.04 1.02 1.58 0.00 0.36Swaziland 0.91 … … … … 0.00 … … … …Togo 0.22 0.47 0.91 0.00 1.60 0.00 0.04 0.14 0.00 0.02Tunisia 2.27 0.44 0.72 0.00 3.43 0.08 0.07 0.19 0.01 0.09Uganda 0.08 … … … … 0.01 … … … …United Republic of Tanzania 0.13 1.01 0.81 0.00 1.95 0.02 0.60 0.84 0.00 0.20Western Sahara … … … … … … … … … …Zambia 0.20 1.43 0.97 0.00 2.60 0.01 0.25 0.30 0.00 0.08Zimbabwe 0.93 0.83 0.81 0.00 2.57 0.04 0.16 0.27 0.00 0.08ASIAAfghanistan 0.03 … … … … 0.00 … … … …Armenia 1.42 0.75 0.15 0.00 2.32 0.02 0.03 0.01 0.00 0.02Azerbaijan 4.20 1.38 0.48 0.01 6.07 0.13 0.17 0.11 0.01 0.13Bahrain 27.03 2.71 0.08 0.26 30.08 0.07 0.03 0.00 0.03 0.06Bangladesh 0.26 0.60 0.24 0.00 1.10 0.14 1.40 0.98 0.00 0.44Bhutan 0.60 … … … … 0.00 … … … …Brunei Darussalam 15.95 5.57 1.00 0.00 22.52 0.02 0.03 0.01 0.00 0.02Cambodia 0.27 1.07 0.28 0.00 1.62 0.01 0.23 0.10 0.00 0.06China 4.31 0.76 0.43 0.09 5.59 20.32 15.08 14.97 20.05 18.89China, Hong Kong SAR 6.03 0.16 0.03 0.05 6.27 0.15 0.02 0.01 0.06 0.11China, Macao SAR 4.73 … … … … 0.01 … … … …Cyprus 8.97 0.39 0.77 0.00 10.13 0.03 0.00 0.02 0.00 0.02Democratic People's Republic of Korea 3.55 0.45 0.98 0.04 5.02 0.30 0.16 0.61 0.14 0.31Georgia 1.07 0.97 0.76 0.00 2.80 0.02 0.07 0.09 0.00 0.03India 1.30 0.65 0.27 0.01 2.23 5.14 10.79 7.94 1.59 6.33Indonesia 1.51 1.02 0.32 0.00 2.85 1.19 3.40 1.85 0.15 1.62Iran (Islamic Republic of) 6.31 1.38 0.96 0.02 8.67 1.57 1.44 1.75 0.26 1.55Iraq 3.11 0.39 0.14 0.02 3.66 0.32 0.17 0.11 0.08 0.27Israel 9.18 0.17 0.26 0.16 9.77 0.23 0.02 0.05 0.19 0.18


TABLE B.8continued



2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

Japan 10.17 0.42 0.18 0.55 11.32 4.70 0.81 0.62 11.82 3.74Jordan 3.94 0.30 0.23 0.00 4.47 0.08 0.02 0.03 0.00 0.06Kazakhstan 11.69 1.87 0.37 0.00 13.93 0.64 0.43 0.15 0.00 0.55Kuwait 35.42 4.42 0.21 0.15 40.20 0.32 0.17 0.01 0.07 0.26Kyrgyzstan 1.08 0.68 0.63 0.01 2.40 0.02 0.05 0.09 0.01 0.03Lao People's Democratic Republic 0.24 … … … … 0.01 … … … …Lebanon 4.28 0.24 0.25 0.00 4.77 0.06 0.01 0.03 0.00 0.05Malaysia 7.15 1.00 0.39 0.02 8.56 0.66 0.39 0.26 0.09 0.57Maldives 2.32 … … … … 0.00 … … … …Mongolia 3.45 1.90 8.96 0.00 14.31 0.03 0.07 0.60 0.00 0.09Myanmar 0.22 1.26 0.54 0.00 2.02 0.04 0.92 0.68 0.00 0.25Nepal 0.12 1.32 0.26 0.00 1.70 0.01 0.55 0.19 0.00 0.12Occupied Palestinian Territory 0.77 … … … … 0.01 … … … …Oman 12.01 1.63 0.44 0.00 14.08 0.11 0.06 0.03 0.00 0.10Pakistan 0.86 0.71 0.51 0.00 2.08 0.48 1.67 2.11 0.10 0.84Philippines 0.89 0.52 0.22 0.00 1.63 0.28 0.68 0.50 0.06 0.36Qatar 52.72 5.86 0.32 0.00 58.90 0.17 0.08 0.01 0.00 0.13Republic of Korea 9.84 0.65 0.46 0.18 11.13 1.71 0.47 0.58 1.46 1.39Saudi Arabia 15.86 2.75 0.33 0.07 19.01 1.33 0.96 0.20 0.26 1.14Singapore 13.95 0.30 1.87 0.30 16.42 0.22 0.02 0.21 0.22 0.18Sri Lanka 0.59 0.52 0.16 0.00 1.27 0.04 0.16 0.08 0.00 0.06Syrian Arab Republic 3.48 0.42 0.49 0.00 4.39 0.24 0.12 0.25 0.00 0.22Tajikistan 0.89 0.50 0.24 0.02 1.65 0.02 0.05 0.04 0.02 0.03Thailand 4.11 1.20 0.42 0.01 5.74 0.98 1.19 0.74 0.16 0.98Timor-Leste 0.18 … … … … 0.00 … … … …Turkey 3.49 0.33 0.67 0.02 4.51 0.90 0.35 1.27 0.25 0.83Turkmenistan 8.62 4.76 0.66 0.05 14.09 0.15 0.35 0.08 0.04 0.18United Arab Emirates 33.16 8.38 0.67 0.12 42.33 0.49 0.52 0.07 0.08 0.45Uzbekistan 4.30 1.97 0.56 0.03 6.86 0.41 0.78 0.39 0.13 0.46Viet Nam 1.22 0.90 0.45 0.00 2.57 0.37 1.14 0.99 0.00 0.55Yemen 0.96 0.43 0.34 0.00 1.73 0.07 0.14 0.19 0.00 0.09EUROPEAlbania 1.46 0.70 0.45 0.02 2.63 0.02 0.03 0.04 0.01 0.02Andorra … … … … … … … … … …Austria 8.84 0.88 0.56 0.40 10.68 0.26 0.11 0.12 0.55 0.23Belarus 6.58 1.70 1.06 0.05 9.39 0.23 0.25 0.27 0.07 0.24Belgium 10.43 0.73 0.92 0.90 12.98 0.40 0.12 0.25 1.57 0.35Bosnia and Herzegovina 6.77 0.75 0.27 0.22 8.01 0.09 0.04 0.03 0.14 0.08Bulgaria 6.07 0.79 0.76 0.08 7.70 0.17 0.09 0.16 0.11 0.15Channel Islands … … … … … … … … … …Croatia 5.31 0.83 0.81 0.16 7.11 0.09 0.06 0.09 0.12 0.08Czech Republic 11.20 1.46 0.64 0.34 13.64 0.41 0.23 0.17 0.59 0.36Denmark 8.64 0.91 1.36 0.27 11.18 0.17 0.07 0.19 0.24 0.16Estonia 13.52 0.91 0.45 0.04 14.92 0.07 0.02 0.02 0.01 0.05Faeroe Islands 14.05 … … … … 0.00 … … … …Finland 10.44 1.04 1.02 0.20 12.70 0.20 0.08 0.14 0.17 0.17France 6.48 0.71 1.28 0.44 8.91 1.43 0.66 2.06 4.52 1.40Germany 9.74 0.70 0.84 0.51 11.79 2.90 0.88 1.83 7.03 2.52Gibraltar … … … … … … … … … …Greece 8.90 0.67 1.18 0.15 10.90 0.36 0.11 0.35 0.27 0.31Holy See … … … … … … … … … …Hungary 5.83 1.10 0.87 0.15 7.95 0.21 0.17 0.23 0.26 0.21Iceland 7.36 1.11 2.19 0.27 10.93 0.01 0.00 0.02 0.01 0.01Ireland 10.58 0.88 2.96 0.49 14.91 0.16 0.06 0.33 0.34 0.16Isle of Man … … … … … … … … … …Italy 8.02 0.63 0.63 0.47 9.75 1.70 0.56 0.98 4.64 1.48Latvia 3.07 1.00 0.60 0.05 4.72 0.03 0.03 0.04 0.02 0.03Liechtenstein … … … … … … … … … …Lithuania 4.10 1.07 0.84 0.04 6.05 0.05 0.06 0.08 0.03 0.05Luxembourg 24.33 0.39 0.17 0.11 25.00 0.04 0.00 0.00 0.01 0.03Malta 6.41 0.25 0.12 0.00 6.78 0.01 0.00 0.00 0.00 0.01Moldova 2.16 0.69 0.26 0.10 3.21 0.03 0.04 0.03 0.06 0.03Monaco … … … … … … … … … …Montenegro … … … … … … … … … …Netherlands 10.72 0.93 1.03 0.32 13.00 0.63 0.23 0.44 0.89 0.55Norway 13.15 2.61 1.01 0.38 17.15 0.22 0.18 0.12 0.30 0.21Poland 7.95 1.57 0.68 0.03 10.23 1.10 0.91 0.69 0.21 1.01Portugal 6.20 0.68 0.66 0.10 7.64 0.24 0.11 0.18 0.18 0.21Romania 4.24 1.08 0.54 0.10 5.96 0.33 0.35 0.31 0.37 0.33Russian Federation 10.58 3.50 0.30 0.40 14.78 5.47 7.59 1.13 9.48 5.47San Marino … … … … … … … … … …Serbia … … … … … … … … … …Slovakia 6.99 0.98 0.51 0.13 8.61 0.14 0.08 0.07 0.12 0.12Slovenia 7.46 0.81 0.55 0.10 8.92 0.05 0.02 0.03 0.04 0.05Spain 8.21 0.88 1.12 0.35 10.56 1.29 0.58 1.28 2.52 1.18Sweden 5.70 0.72 0.67 0.18 7.27 0.19 0.10 0.16 0.27 0.17Switzerland 5.56 0.56 0.38 0.45 6.95 0.15 0.06 0.08 0.55 0.13TFYR Macedonia6 5.52 … … … … 0.04 … … … …

229Data Tables

TABLE B.8continued



2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

Ukraine 6.94 1.61 0.49 0.03 9.07 1.18 1.15 0.61 0.23 1.11United Kingdom 9.19 0.65 1.09 0.23 11.16 2.00 0.60 1.73 2.35 1.74LATIN AMERICA AND THE CARIBBEANAnguilla … … … … … … … … … …Antigua and Barbuda 4.91 … … … … 0.00 … … … …Argentina 4.10 2.44 2.15 0.02 8.71 0.57 1.43 2.20 0.16 0.87Aruba 22.84 … … … … 0.01 … … … …Bahamas 6.47 … … … … 0.01 … … … …Barbados 5.19 … … … … 0.00 … … … …Belize 2.80 … … … … 0.00 … … … …Bolivia 1.04 2.95 3.08 0.00 7.07 0.03 0.41 0.75 0.00 0.17Brazil 1.88 2.27 1.61 0.04 5.80 1.26 6.39 7.93 1.30 2.79British Virgin Islands … … … … … … … … … …Cayman Islands 11.31 … … … … 0.00 … … … …Chile 3.64 1.20 0.77 0.00 5.61 0.21 0.30 0.33 0.00 0.24Colombia 1.37 1.43 0.57 0.01 3.38 0.21 0.93 0.65 0.06 0.38Costa Rica 1.68 0.57 0.66 0.00 2.91 0.03 0.04 0.08 0.00 0.03Cuba 2.22 0.85 0.74 0.01 3.82 0.09 0.14 0.22 0.02 0.11Dominica 1.58 … … … … 0.00 … … … …Dominican Republic 2.08 0.63 0.30 0.00 3.01 0.07 0.09 0.08 0.00 0.07Ecuador 2.35 0.99 0.65 0.00 3.99 0.11 0.20 0.22 0.00 0.13El Salvador 1.04 0.53 0.37 0.00 1.94 0.02 0.05 0.06 0.00 0.03Falkland Islands (Malvinas) … … … … … … … … … …French Guiana … … … … … … … … … …Grenada 2.28 … … … … 0.00 … … … …Guadeloupe … … … … … … … … … …Guatemala 0.93 0.71 0.63 0.00 2.27 0.04 0.14 0.21 0.00 0.07Guyana 1.95 … … … … 0.01 … … … …Haiti 0.19 0.40 0.46 0.00 1.05 0.01 0.06 0.11 0.00 0.03Honduras 1.13 0.78 0.56 0.00 2.47 0.03 0.08 0.10 0.00 0.04Jamaica 3.83 0.44 0.38 0.00 4.65 0.04 0.02 0.03 0.00 0.03Martinique … … … … … … … … … …Mexico 4.16 1.17 0.73 0.03 6.09 1.55 1.82 1.99 0.53 1.62Montserrat … … … … … … … … … …Netherlands Antilles 20.12 0.59 0.32 0.00 21.03 0.01 0.00 0.00 0.00 0.01Nicaragua 0.76 1.16 0.59 0.00 2.51 0.02 0.10 0.08 0.00 0.04Panama 1.85 0.94 0.64 0.00 3.43 0.02 0.05 0.05 0.00 0.03Paraguay 0.65 3.01 2.18 0.00 5.84 0.01 0.27 0.34 0.00 0.09Peru 1.33 0.77 0.67 0.00 2.77 0.13 0.33 0.49 0.01 0.20Puerto Rico … … … … … … … … … …Saint Kitts and Nevis 2.83 … … … … 0.00 … … … …Saint Lucia 2.27 … … … … 0.00 … … … …Saint Vincent and the Grenadines 1.78 … … … … 0.00 … … … …Suriname 4.76 … … … … 0.01 … … … …Trinidad and Tobago 23.46 2.90 0.27 0.00 26.63 0.11 0.06 0.01 0.00 0.09Turks and Caicos Islands … … … … … … … … … …United States Virgin Islands … … … … … … … … … …Uruguay 1.81 5.35 4.73 0.01 11.90 0.02 0.27 0.41 0.00 0.10Venezuela (Bolivarian Republic of) 5.73 2.47 1.00 0.09 9.29 0.55 1.00 0.70 0.39 0.64NORTHERN AMERICABermuda 8.87 … … … … 0.00 … … … …Canada 17.31 3.21 1.59 0.34 22.45 2.02 1.57 1.36 1.84 1.88Greenland 9.78 … … … … 0.00 … … … …Saint-Pierre-et-Miquelon … … … … … … … … … …United States of America 19.75 2.74 1.54 0.37 24.40 21.10 12.27 12.05 18.16 18.66OCEANIAAmerican Samoa … … … … … … … … … …Australia 17.92 5.73 5.61 0.22 29.48 1.32 1.77 3.02 0.77 1.56Cook Islands … … … … … … … … … …Fiji 2.01 … … … … 0.01 … … … …French Polynesia 3.34 … … … … 0.00 … … … …Guam … … … … … … … … … …Kiribati 0.28 … … … … 0.00 … … … …Marshall Islands 1.51 … … … … 0.00 … … … …Micronesia (Federated States of) … … … … … … … … … …Nauru … … … … … … … … … …New Caledonia 11.94 … … … … 0.01 … … … …New Zealand 7.28 6.65 6.76 0.20 20.89 0.11 0.42 0.74 0.14 0.22Niue … … … … … … … … … …Northern Mariana Islands … … … … … … … … … …Palau 5.87 … … … … 0.00 … … … …Papua New Guinea 0.75 … … … … 0.02 … … … …Pitcairn … … … … … … … … … …Samoa 0.88 … … … … 0.00 … … … …Solomon Islands 0.38 … … … … 0.00 … … … …Tokelau … … … … … … … … … …Tonga 1.30 … … … … 0.00 … … … …


TABLE B.8continued



2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

Tuvalu … … … … … … … … … …Vanuatu 0.41 … … … … 0.00 … … … …Wallis and Futuna Islands … … … … … … … … … …

Source: World Bank (2010). Data retrieved 17 June 2010 from World Development Indicators Online (WDI) database.

Notes:(1) Percentages are based on a total of 27,668,659 tonnes allocated to countries, exluding 1,537,085 tonnes emitted globally and not accounted for in national inventories.(2) Percentages are based on a total of 6,603,040 tonnes allocated to countries, exluding 4,450 tonnes emitted globally and not accounted for in national inventories.(3) Percentages are based on a total of 3,786,400 tonnes allocated to countries, exluding 1,400 tonnes emitted globally and not accounted for in national inventories.(4) Percentages are based on a total of 597,090 tonnes allocated to countries, exluding 4,800 tonnes emitted globally and not accounted for in national inventories.(5) Percentages are based on a total of 38,655,189 tonnes allocated to countries, exluding 1,547,735 tonnes emitted globally and not accounted for in national inventories.(6) The former Yugoslav Republic of Macedonia.

231Data Tables

CITY LEVEL DATATABLE C.1 Urban Agglomerations with 750,000 Inhabitants or More: Population Size and Rate of Change

Estimates and projections ('000) Annual rate of change (%) Share in national urban population (%)

2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

AFRICAAlgeria El Djazaïr (Algiers) 2,254 2,800 3,371 2.17 1.86 12.4 11.9 11.5Algeria Wahran (Oran) 705 770 902 0.88 1.58 3.9 3.3 3.1Angola Huambo 578 1,034 1,551 5.82 4.05 8.3 9.3 9.6Angola Luanda 2,591 4,772 7,080 6.11 3.95 37.0 42.9 43.7Benin Cotonou 642 844 1,217 2.74 3.66 25.1 21.8 21.2Burkina Faso Ouagadougou 921 1,908 3,457 7.28 5.94 44.2 45.6 46.0Cameroon Douala 1,432 2,125 2,815 3.95 2.81 18.1 18.2 17.7Cameroon Yaoundé 1,192 1,801 2,392 4.13 2.84 15.1 15.5 15.0Chad N'Djaména 647 829 1,170 2.48 3.45 32.9 26.1 23.1Congo Brazzaville 986 1,323 1,703 2.94 2.52 55.7 56.7 54.6Côte d’Ivoire Abidjan 3,032 4,125 5,550 3.08 2.97 40.3 37.8 35.6Côte d’Ivoire Yamoussoukro 348 885 1,559 9.34 5.66 4.6 8.1 10.0Democratic Republic of the Congo Kananga 552 878 1,324 4.64 4.11 3.6 3.7 3.6Democratic Republic of the Congo Kinshasa 5,611 8,754 12,788 4.45 3.79 37.0 36.6 34.7Democratic Republic of the Congo Kisangani 535 812 1,221 4.17 4.07 3.5 3.4 3.3Democratic Republic of the Congo Lubumbashi 995 1,543 2,304 4.39 4.01 6.6 6.5 6.3Democratic Republic of the Congo Mbuji-Mayi 924 1,488 2,232 4.76 4.05 6.1 6.2 6.1Egypt Al-Iskandariyah (Alexandria) 3,592 4,387 5,201 2.00 1.70 12.0 12.0 11.5Egypt Al-Qahirah (Cairo) 10,170 11,001 12,540 0.79 1.31 33.9 30.0 27.7Ethiopia Addis Ababa 2,376 2,930 3,981 2.10 3.07 24.3 20.7 19.1Ghana Accra 1,674 2,342 3,110 3.36 2.84 19.5 18.7 18.0Ghana Kumasi 1,187 1,834 2,448 4.35 2.89 13.8 14.6 14.2Guinea Conakry 1,219 1,653 2,427 3.05 3.84 46.8 45.3 43.5Kenya Mombasa 687 1,003 1,479 3.78 3.88 11.1 11.1 10.7Kenya Nairobi 2,230 3,523 5,192 4.57 3.88 35.9 38.9 37.6Liberia Monrovia 836 827 807 -0.11 -0.24 66.8 42.2 29.5Libyan Arab Jamahiriya Tarabulus (Tripoli) 1,022 1,108 1,286 0.81 1.49 25.0 21.7 20.8Madagascar Antananarivo 1,361 1,879 2,658 3.23 3.47 32.9 30.9 29.7Mali Bamako 1,110 1,699 2,514 4.26 3.92 37.2 35.6 34.3Morocco Agadir 609 783 948 2.51 1.91 4.0 4.2 4.1Morocco Dar-el-Beida (Casablanca) 3,043 3,284 3,816 0.76 1.50 19.8 17.4 16.5Morocco Fès 870 1,065 1,277 2.02 1.82 5.7 5.6 5.5Morocco Marrakech 755 928 1,114 2.06 1.83 4.9 4.9 4.8Morocco Rabat 1,507 1,802 2,139 1.79 1.71 9.8 9.6 9.2Morocco Tanger 591 788 958 2.86 1.96 3.8 4.2 4.1Mozambique Maputo 1,096 1,655 2,350 4.12 3.51 19.6 18.4 17.8Mozambique Matola 504 793 1,139 4.54 3.62 9.0 8.8 8.6Niger Niamey 680 1,048 1,643 4.33 4.50 38.1 38.5 37.2Nigeria Aba 614 785 1,058 2.46 2.98 1.2 1.0 1.0Nigeria Abuja 832 1,995 2,977 8.75 4.00 1.6 2.5 2.7Nigeria Benin City 975 1,302 1,758 2.89 3.00 1.8 1.7 1.6Nigeria Ibadan 2,236 2,837 3,760 2.38 2.82 4.2 3.6 3.4Nigeria Ilorin 653 835 1,125 2.46 2.98 1.2 1.1 1.0Nigeria Jos 627 802 1,081 2.47 2.98 1.2 1.0 1.0Nigeria Kaduna 1,220 1,561 2,087 2.46 2.90 2.3 2.0 1.9Nigeria Kano 2,658 3,395 4,495 2.45 2.81 5.0 4.3 4.1Nigeria Lagos 7,233 10,578 14,162 3.80 2.92 13.6 13.4 12.9Nigeria Maiduguri 758 970 1,303 2.47 2.95 1.4 1.2 1.2Nigeria Ogbomosho 798 1,032 1,389 2.57 2.97 1.5 1.3 1.3Nigeria Port Harcourt 863 1,104 1,482 2.46 2.94 1.6 1.4 1.3Nigeria Zaria 752 963 1,295 2.47 2.96 1.4 1.2 1.2Rwanda Kigali 497 939 1,392 6.36 3.94 45.3 48.5 46.5Senegal Dakar 2,029 2,863 3,796 3.44 2.82 50.8 52.5 50.5Sierra Leone Freetown 688 901 1,219 2.70 3.02 45.8 40.2 38.9Somalia Muqdisho (Mogadishu) 1,201 1,500 2,156 2.22 3.63 48.9 42.8 40.9South Africa Cape Town 2,715 3,405 3,701 2.26 0.83 10.6 10.9 10.6South Africa Durban 2,370 2,879 3,133 1.95 0.85 9.3 9.2 8.9South Africa Ekurhuleni (East Rand) 2,326 3,202 3,497 3.20 0.88 9.1 10.3 10.0South Africa Johannesburg 2,732 3,670 3,996 2.95 0.85 10.7 11.8 11.4South Africa Port Elizabeth 958 1,068 1,173 1.09 0.94 3.8 3.4 3.3South Africa Pretoria 1,084 1,429 1,575 2.76 0.97 4.2 4.6 4.5South Africa Vereeniging 897 1,143 1,262 2.42 0.99 3.5 3.7 3.6Sudan Al-Khartum (Khartoum) 3,949 5,172 7,005 2.70 3.03 33.9 29.9 28.2Togo Lomé 1,020 1,667 2,398 4.91 3.64 53.2 56.6 56.3Uganda Kampala 1,097 1,598 2,504 3.76 4.49 37.2 35.6 33.9United Republic of Tanzania Dar es Salaam 2,116 3,349 5,103 4.59 4.21 27.8 28.2 26.9Zambia Lusaka 1,073 1,451 1,941 3.02 2.91 29.5 30.7 29.5Zimbabwe Harare 1,379 1,632 2,170 1.68 2.85 32.8 33.7 31.7ASIAAfghanistan Kabul 1,963 3,731 5,665 6.42 4.18 47.3 56.7 54.2Armenia Yerevan 1,111 1,112 1,132 0.01 0.18 55.9 56.0 54.2Azerbaijan Baku 1,806 1,972 2,190 0.88 1.05 43.4 42.5 41.1Bangladesh Chittagong 3,308 4,962 6,447 4.05 2.62 10.0 10.8 10.3Bangladesh Dhaka 10,285 14,648 18,721 3.54 2.45 31.0 31.7 29.8Bangladesh Khulna 1,285 1,682 2,211 2.69 2.73 3.9 3.6 3.5Bangladesh Rajshahi 678 878 1,164 2.58 2.82 2.0 1.9 1.9Cambodia Phnum Pénh (Phnom Penh) 1,160 1,562 2,093 2.98 2.93 53.8 51.6 49.7


TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

China Anshan, Liaoning 1,384 1,663 1,990 1.84 1.80 0.3 0.3 0.3China Anyang 753 1,130 1,326 4.06 1.60 0.2 0.2 0.2China Baoding 884 1,213 1,524 3.16 2.28 0.2 0.2 0.2China Baotou 1,406 1,932 2,243 3.18 1.49 0.3 0.3 0.3China Beijing 9,757 12,385 14,296 2.39 1.43 2.2 1.9 1.8China Bengbu 687 914 1,142 2.85 2.23 0.2 0.1 0.1China Benxi 857 969 1,136 1.23 1.59 0.2 0.2 0.1China Changchun 2,730 3,597 4,409 2.76 2.04 0.6 0.6 0.6China Changde 735 849 994 1.44 1.58 0.2 0.1 0.1China Changsha, Hunan 2,077 2,415 2,885 1.51 1.78 0.5 0.4 0.4China Changzhou, Jiangsu 1,068 2,062 2,466 6.58 1.79 0.2 0.3 0.3China Chengdu 3,919 4,961 5,886 2.36 1.71 0.9 0.8 0.7China Chifeng 677 842 1,020 2.18 1.92 0.1 0.1 0.1China Chongqing 6,039 9,401 10,514 4.43 1.12 1.3 1.5 1.3China Cixi 650 781 928 1.83 1.72 0.1 0.1 0.1China Dalian 2,833 3,306 3,896 1.54 1.64 0.6 0.5 0.5China Dandong 679 795 947 1.58 1.75 0.1 0.1 0.1China Daqing 1,082 1,546 1,981 3.57 2.48 0.2 0.2 0.3China Datong, Shanxi 1,049 1,251 1,500 1.76 1.82 0.2 0.2 0.2China Dongguan, Guangdong 3,631 5,347 6,483 3.87 1.93 0.8 0.8 0.8China Foshan 754 4,969 5,903 18.86 1.72 0.2 0.8 0.8China Fushun, Liaoning 1,358 1,378 1,544 0.15 1.14 0.3 0.2 0.2China Fuxin 667 821 999 2.08 1.96 0.1 0.1 0.1China Fuyang 695 874 1,045 2.29 1.79 0.2 0.1 0.1China Fuzhou, Fujian 1,978 2,787 3,509 3.43 2.30 0.4 0.4 0.4China Guangzhou, Guangdong 7,330 8,884 10,409 1.92 1.58 1.6 1.4 1.3China Guilin 757 991 1,231 2.69 2.17 0.2 0.2 0.2China Guiyang 1,860 2,154 2,519 1.47 1.57 0.4 0.3 0.3China Haerbin 3,419 4,251 4,800 2.18 1.21 0.8 0.7 0.6China Handan 811 1,249 1,652 4.32 2.80 0.2 0.2 0.2China Hangzhou 2,411 3,860 4,470 4.71 1.47 0.5 0.6 0.6China Hefei 1,532 2,404 2,850 4.51 1.70 0.3 0.4 0.4China Hengyang 793 1,099 1,393 3.26 2.37 0.2 0.2 0.2China Huizhou 551 1,384 1,713 9.22 2.13 0.1 0.2 0.2China Huai'an 818 998 1,195 1.99 1.80 0.2 0.2 0.2China Huaibei 617 962 1,275 4.44 2.82 0.1 0.2 0.2China Huainan 1,049 1,396 1,738 2.86 2.19 0.2 0.2 0.2China Hohhot 1,005 1,589 2,118 4.58 2.87 0.2 0.2 0.3China Huludao 529 795 1,045 4.08 2.74 0.1 0.1 0.1China Jiamusi 619 817 1,020 2.78 2.22 0.1 0.1 0.1China Jiangmen 519 1,103 1,355 7.55 2.06 0.1 0.2 0.2China Jiaozuo 631 900 1,155 3.55 2.49 0.1 0.1 0.1China Jieyang 608 855 1,081 3.41 2.35 0.1 0.1 0.1China Jilin 1,435 1,888 2,338 2.74 2.14 0.3 0.3 0.3China Jinan, Shandong 2,592 3,237 3,813 2.22 1.64 0.6 0.5 0.5China Jingzhou 761 1,039 1,302 3.12 2.25 0.2 0.2 0.2China Jining, Shandong 856 1,077 1,304 2.30 1.91 0.2 0.2 0.2China Jinjiang 456 858 1,216 6.31 3.49 0.1 0.1 0.2China Jinzhou 770 857 998 1.07 1.52 0.2 0.1 0.1China Jixi, Heilongjiang 823 1,042 1,278 2.36 2.04 0.2 0.2 0.2China Kaohsiung 1,488 1,611 1,850 0.79 1.38 0.3 0.3 0.2China Kunming 2,561 3,116 3,691 1.96 1.69 0.6 0.5 0.5China Lanzhou 1,890 2,285 2,724 1.90 1.76 0.4 0.4 0.3China Lianyungang 567 878 1,105 4.37 2.30 0.1 0.1 0.1China Linyi, Shandong 1,932 2,177 2,594 1.19 1.75 0.4 0.3 0.3China Liuzhou 1,027 1,352 1,675 2.75 2.14 0.2 0.2 0.2China Lufeng 556 889 1,192 4.69 2.94 0.1 0.1 0.2China Luoyang 1,213 1,539 1,875 2.38 1.97 0.3 0.2 0.2China Luzhou 649 850 1,049 2.69 2.10 0.1 0.1 0.1China Maoming 617 803 983 2.63 2.03 0.1 0.1 0.1China Mianyang, Sichuan 758 1,006 1,244 2.83 2.12 0.2 0.2 0.2China Mudanjiang 665 783 933 1.63 1.75 0.1 0.1 0.1China Nanchang 1,648 2,701 3,236 4.94 1.81 0.4 0.4 0.4China Nanchong 606 808 1,006 2.88 2.19 0.1 0.1 0.1China Nanjing, Jiangsu 3,472 4,519 5,524 2.64 2.01 0.8 0.7 0.7China Nanning 1,445 2,096 2,508 3.72 1.79 0.3 0.3 0.3China Nantong 607 1,423 1,734 8.52 1.98 0.1 0.2 0.2China Nanyang, Henan 672 867 1,060 2.55 2.01 0.1 0.1 0.1China Neijiang 685 883 1,088 2.54 2.09 0.2 0.1 0.1China Ningbo 1,303 2,217 2,782 5.31 2.27 0.3 0.3 0.4China Panjin 593 813 1,028 3.16 2.35 0.1 0.1 0.1China Pingdingshan, Henan 852 1,024 1,222 1.84 1.77 0.2 0.2 0.2China Puning 603 911 1,172 4.13 2.52 0.1 0.1 0.1China Putian 439 1,085 1,241 9.05 1.34 0.1 0.2 0.2China Qingdao 2,659 3,323 3,923 2.23 1.66 0.6 0.5 0.5China Qinhuangdao 702 893 1,088 2.41 1.98 0.2 0.1 0.1China Qiqihaer 1,331 1,588 1,894 1.77 1.76 0.3 0.2 0.2China Quanzhou 728 1,068 1,367 3.83 2.47 0.2 0.2 0.2China Rizhao 613 816 1,014 2.87 2.17 0.1 0.1 0.1China Shanghai 13,224 16,575 19,094 2.26 1.41 2.9 2.6 2.4China Shantou 1,247 3,502 3,983 10.33 1.29 0.3 0.6 0.5

233Data Tables

TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

China Shaoguan 517 845 995 4.91 1.63 0.1 0.1 0.1China Shaoxing 608 853 1,077 3.39 2.33 0.1 0.1 0.1China Shenyang 4,562 5,166 6,108 1.24 1.68 1.0 0.8 0.8China Shenzhen 6,069 9,005 10,585 3.95 1.62 1.3 1.4 1.3China Shijiazhuang 1,914 2,487 3,044 2.62 2.02 0.4 0.4 0.4China Suzhou, Jiangsu 1,316 2,398 2,842 6.00 1.70 0.3 0.4 0.4China Taian, Shandong 910 1,239 1,548 3.09 2.23 0.2 0.2 0.2China Taichung 978 1,251 1,538 2.46 2.07 0.2 0.2 0.2China Tainan 723 777 895 0.72 1.41 0.2 0.1 0.1China Taipei 2,630 2,633 2,921 0.01 1.04 0.6 0.4 0.4China Taiyuan, Shanxi 2,503 3,154 3,812 2.31 1.89 0.6 0.5 0.5China Taizhou, Jiangsu 535 795 1,028 3.95 2.57 0.1 0.1 0.1China Taizhou, Zhejiang 1,190 1,338 1,566 1.17 1.57 0.3 0.2 0.2China Tangshan, Hebei 1,390 1,870 2,335 2.97 2.22 0.3 0.3 0.3China Tianjin 6,670 7,884 9,216 1.67 1.56 1.5 1.2 1.2China Ürümqi (Wulumqi) 1,705 2,398 3,040 3.41 2.37 0.4 0.4 0.4China Weifang 1,235 1,698 2,131 3.18 2.27 0.3 0.3 0.3China Wenzhou 1,565 2,659 3,436 5.30 2.56 0.3 0.4 0.4China Wuhan 6,638 7,681 8,868 1.46 1.44 1.5 1.2 1.1China Wuhu, Anhui 634 908 1,169 3.59 2.53 0.1 0.1 0.1China Wuxi, Jiangsu 1,409 2,682 3,206 6.44 1.78 0.3 0.4 0.4China Xiamen 1,416 2,207 2,926 4.44 2.82 0.3 0.3 0.4China Xi'an, Shaanxi 3,690 4,747 5,414 2.52 1.31 0.8 0.7 0.7China Xiangfan, Hubei 847 1,399 1,674 5.02 1.79 0.2 0.2 0.2China Xiangtan, Hunan 698 926 1,155 2.83 2.21 0.2 0.1 0.1China Xianyang, Shaanxi 790 1,019 1,247 2.55 2.02 0.2 0.2 0.2China Xining 844 1,261 1,649 4.02 2.68 0.2 0.2 0.2China Xinxiang 762 1,016 1,267 2.88 2.21 0.2 0.2 0.2China Xuzhou 1,367 2,142 2,833 4.49 2.80 0.3 0.3 0.4China Yancheng, Jiangsu 671 1,289 1,622 6.53 2.30 0.1 0.2 0.2China Yangzhou 702 1,080 1,430 4.32 2.80 0.2 0.2 0.2China Yantai 1,218 1,526 1,836 2.25 1.85 0.3 0.2 0.2China Yichang 692 959 1,132 3.26 1.66 0.2 0.2 0.1China Yichun, Heilongjiang 815 779 856 -0.45 0.94 0.2 0.1 0.1China Yinchuan 571 911 1,225 4.67 2.96 0.1 0.1 0.2China Yingkou 624 848 1,072 3.07 2.34 0.1 0.1 0.1China Yiyang, Hunan 678 820 974 1.90 1.72 0.1 0.1 0.1China Yueyang 881 1,096 1,317 2.18 1.84 0.2 0.2 0.2China Zaozhuang 853 1,175 1,473 3.20 2.26 0.2 0.2 0.2China Zhangjiakou 797 1,043 1,294 2.69 2.16 0.2 0.2 0.2China Zhanjiang 818 996 1,198 1.97 1.85 0.2 0.2 0.2China Zhengzhou 2,438 2,966 3,519 1.96 1.71 0.5 0.5 0.4China Zhenjiang, Jiangsu 679 1,007 1,308 3.94 2.62 0.1 0.2 0.2China Zhongshan 1,376 2,211 2,927 4.75 2.81 0.3 0.3 0.4China Zhuhai 799 1,252 1,420 4.49 1.26 0.2 0.2 0.2China Zhuzhou 819 1,025 1,244 2.24 1.94 0.2 0.2 0.2China Zibo 1,874 2,456 3,004 2.70 2.01 0.4 0.4 0.4China Zigong 592 918 1,067 4.39 1.50 0.1 0.1 0.1China Zunyi 541 843 1,118 4.44 2.82 0.1 0.1 0.1China, Hong Kong SAR Hong Kong 6,667 7,069 7,701 0.59 0.86 100.0 100.0 100.0Democratic People’s Rep. of Korea P'yongyang 2,777 2,833 2,894 0.20 0.21 20.4 19.6 18.8Georgia Tbilisi 1,100 1,120 1,138 0.18 0.16 44.0 50.3 52.3India Agra 1,293 1,703 2,089 2.75 2.04 0.4 0.5 0.5India Ahmadabad 4,427 5,717 6,892 2.56 1.87 1.5 1.6 1.5India Aligarh 653 863 1,068 2.79 2.13 0.2 0.2 0.2India Allahabad 1,035 1,277 1,570 2.10 2.07 0.4 0.4 0.3India Amritsar 990 1,297 1,597 2.70 2.08 0.3 0.4 0.3India Asansol 1,065 1,423 1,751 2.90 2.07 0.4 0.4 0.4India Aurangabad 868 1,198 1,478 3.22 2.10 0.3 0.3 0.3India Bangalore 5,567 7,218 8,674 2.60 1.84 1.9 2.0 1.9India Bareilly 722 868 1,072 1.84 2.11 0.3 0.2 0.2India Bhiwandi 603 859 1,066 3.54 2.16 0.2 0.2 0.2India Bhopal 1,426 1,843 2,257 2.57 2.03 0.5 0.5 0.5India Bhubaneswar 637 912 1,131 3.59 2.15 0.2 0.3 0.2India Kolkata (Calcutta) 13,058 15,552 18,449 1.75 1.71 4.5 4.3 4.0India Chandigarh 791 1,049 1,296 2.82 2.11 0.3 0.3 0.3India Jammu 588 857 1,064 3.77 2.16 0.2 0.2 0.2India Chennai (Madras) 6,353 7,547 9,043 1.72 1.81 2.2 2.1 2.0India Coimbatore 1,420 1,807 2,212 2.41 2.02 0.5 0.5 0.5India Delhi 15,730 22,157 26,272 3.43 1.70 5.5 6.1 5.7India Dhanbad 1,046 1,328 1,633 2.39 2.07 0.4 0.4 0.4India Durg-Bhilainagar 905 1,172 1,445 2.59 2.09 0.3 0.3 0.3India Guwahati (Gauhati) 797 1,053 1,300 2.79 2.11 0.3 0.3 0.3India Gwalior 855 1,039 1,280 1.95 2.09 0.3 0.3 0.3India Hubli-Dharwad 776 946 1,168 1.98 2.11 0.3 0.3 0.3India Hyderabad 5,445 6,751 8,110 2.15 1.83 1.9 1.9 1.8India Indore 1,597 2,173 2,659 3.08 2.02 0.6 0.6 0.6India Jabalpur 1,100 1,367 1,679 2.17 2.06 0.4 0.4 0.4India Jaipur 2,259 3,131 3,813 3.26 1.97 0.8 0.9 0.8India Jalandhar 694 917 1,134 2.79 2.12 0.2 0.3 0.2India Jamshedpur 1,081 1,387 1,705 2.49 2.06 0.4 0.4 0.4


TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

India Jodhpur 842 1,061 1,308 2.31 2.10 0.3 0.3 0.3India Kanpur 2,641 3,364 4,084 2.42 1.94 0.9 0.9 0.9India Kochi (Cochin) 1,340 1,610 1,971 1.83 2.03 0.5 0.4 0.4India Kota 692 884 1,093 2.45 2.12 0.2 0.2 0.2India Kozhikode (Calicut) 875 1,007 1,240 1.41 2.08 0.3 0.3 0.3India Lucknow 2,221 2,873 3,497 2.57 1.97 0.8 0.8 0.8India Ludhiana 1,368 1,760 2,156 2.52 2.03 0.5 0.5 0.5India Madurai 1,187 1,365 1,674 1.40 2.04 0.4 0.4 0.4India Meerut 1,143 1,494 1,836 2.68 2.06 0.4 0.4 0.4India Moradabad 626 845 1,048 3.00 2.15 0.2 0.2 0.2India Mumbai (Bombay) 16,086 20,041 23,719 2.20 1.68 5.6 5.5 5.1India Mysore 776 942 1,163 1.94 2.11 0.3 0.3 0.3India Nagpur 2,089 2,607 3,175 2.22 1.97 0.7 0.7 0.7India Nashik 1,117 1,588 1,954 3.52 2.07 0.4 0.4 0.4India Patna 1,658 2,321 2,839 3.36 2.01 0.6 0.6 0.6India Pune (Poona) 3,655 5,002 6,050 3.14 1.90 1.3 1.4 1.3India Raipur 680 943 1,167 3.27 2.13 0.2 0.3 0.3India Rajkot 974 1,357 1,672 3.32 2.09 0.3 0.4 0.4India Ranchi 844 1,119 1,380 2.82 2.10 0.3 0.3 0.3India Salem 736 932 1,152 2.36 2.12 0.3 0.3 0.2India Solapur 853 1,133 1,398 2.84 2.10 0.3 0.3 0.3India Srinagar 954 1,216 1,497 2.43 2.08 0.3 0.3 0.3India Surat 2,699 4,168 5,071 4.35 1.96 0.9 1.1 1.1India Thiruvananthapuram 885 1,006 1,239 1.28 2.08 0.3 0.3 0.3India Tiruchirappalli 837 1,010 1,245 1.88 2.09 0.3 0.3 0.3India Vadodara 1,465 1,872 2,292 2.45 2.02 0.5 0.5 0.5India Varanasi (Benares) 1,199 1,432 1,756 1.78 2.04 0.4 0.4 0.4India Vijayawada 999 1,207 1,484 1.89 2.07 0.3 0.3 0.3India Visakhapatnam 1,309 1,625 1,992 2.16 2.04 0.5 0.4 0.4Indonesia Bandar Lampung 743 799 903 0.73 1.22 0.9 0.8 0.7Indonesia Bandung 2,138 2,412 2,739 1.21 1.27 2.5 2.3 2.2Indonesia Bogor 751 1,044 1,251 3.29 1.81 0.9 1.0 1.0Indonesia Jakarta 8,390 9,210 10,256 0.93 1.08 9.7 8.9 8.4Indonesia Malang 757 786 891 0.38 1.25 0.9 0.8 0.7Indonesia Medan 1,912 2,131 2,419 1.08 1.27 2.2 2.1 2.0Indonesia Palembang 1,459 1,244 1,356 -1.59 0.86 1.7 1.2 1.1Indonesia Semarang 1,427 1,296 1,424 -0.96 0.94 1.7 1.3 1.2Indonesia Surabaya 2,611 2,509 2,738 -0.40 0.87 3.0 2.4 2.2Indonesia Pekan Baru 588 891 1,128 4.16 2.36 0.7 0.9 0.9Indonesia Ujung Pandang 1,031 1,294 1,512 2.27 1.56 1.2 1.3 1.2Iran (Islamic Republic of) Ahvaz 868 1,060 1,249 2.00 1.64 2.0 2.0 2.0Iran (Islamic Republic of) Esfahan 1,382 1,742 2,056 2.32 1.66 3.2 3.3 3.2Iran (Islamic Republic of) Karaj 1,087 1,584 1,937 3.77 2.01 2.5 3.0 3.0Iran (Islamic Republic of) Kermanshah 729 837 974 1.38 1.52 1.7 1.6 1.5Iran (Islamic Republic of) Mashhad 2,073 2,652 3,128 2.46 1.65 4.8 5.0 4.9Iran (Islamic Republic of) Qom 843 1,042 1,232 2.12 1.67 2.0 2.0 1.9Iran (Islamic Republic of) Shiraz 1,115 1,299 1,510 1.53 1.51 2.6 2.4 2.4Iran (Islamic Republic of) Tabriz 1,264 1,483 1,724 1.60 1.51 2.9 2.8 2.7Iran (Islamic Republic of) Tehran 6,880 7,241 8,059 0.51 1.07 16.0 13.6 12.7Iraq Al-Basrah (Basra) 759 923 1,139 1.96 2.10 4.5 4.4 4.3Iraq Al-Mawsil (Mosul) 1,056 1,447 1,885 3.15 2.64 6.3 6.9 7.0Iraq Baghdad 5,200 5,891 7,321 1.25 2.17 31.1 28.3 27.3Iraq Irbil (Erbil) 757 1,009 1,301 2.87 2.54 4.5 4.8 4.9Iraq Sulaimaniya 580 836 1,121 3.66 2.93 3.5 4.0 4.2Israel Hefa (Haifa) 888 1,036 1,144 1.54 0.99 16.0 15.5 14.9Israel Jerusalem 651 782 901 1.83 1.42 11.7 11.7 11.7Israel Tel Aviv-Yafo (Tel Aviv-Jaffa) 2,752 3,272 3,689 1.73 1.20 49.5 48.9 48.1Japan Fukuoka-Kitakyushu 2,716 2,816 2,834 0.36 0.06 3.3 3.3 3.3Japan Hiroshima 2,044 2,081 2,088 0.18 0.03 2.5 2.5 2.4Japan Kyoto 1,806 1,804 1,804 -0.01 0.00 2.2 2.1 2.1Japan Nagoya 3,122 3,267 3,295 0.45 0.09 3.8 3.8 3.8Japan Osaka-Kobe 11,165 11,337 11,368 0.15 0.03 13.5 13.4 13.2Japan Sapporo 2,508 2,687 2,721 0.69 0.13 3.0 3.2 3.2Japan Sendai 2,184 2,376 2,413 0.84 0.15 2.6 2.8 2.8Japan Tokyo 34,450 36,669 37,088 0.62 0.11 41.7 43.2 43.2Jordan Amman 1,007 1,105 1,272 0.93 1.41 26.5 21.7 21.2Kazakhstan Almaty 1,159 1,383 1,554 1.77 1.17 13.8 15.0 14.9Kuwait Al Kuwayt (Kuwait City) 1,499 2,305 2,790 4.30 1.91 68.5 76.8 76.7Kyrgyzstan Bishkek 770 864 967 1.15 1.13 44.2 45.0 43.9Lebanon Bayrut (Beirut) 1,487 1,937 2,090 2.64 0.76 45.8 52.2 51.4Malaysia Johore Bharu 630 999 1,295 4.61 2.60 4.4 5.0 5.2Malaysia Klang 631 1,128 1,503 5.81 2.87 4.4 5.6 6.0Malaysia Kuala Lumpur 1,306 1,519 1,820 1.51 1.81 9.1 7.5 7.2Mongolia Ulaanbaatar 764 966 1,129 2.35 1.56 56.3 57.7 56.2Myanmar Mandalay 810 1,034 1,331 2.44 2.52 6.3 6.1 5.9Myanmar Nay Pyi Taw — 1,024 1,344 .. 2.72 — 6.0 6.0Myanmar Yangon 3,553 4,350 5,456 2.02 2.27 27.4 25.6 24.2Nepal Kathmandu 644 1,037 1,589 4.76 4.27 19.6 18.7 18.2Pakistan Faisalabad 2,140 2,849 3,704 2.86 2.62 4.4 4.3 4.1Pakistan Gujranwala 1,224 1,652 2,165 3.00 2.70 2.5 2.5 2.4Pakistan Hyderabad 1,222 1,590 2,084 2.63 2.71 2.5 2.4 2.3

235Data Tables

TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

Pakistan Islamabad 595 856 1,132 3.64 2.79 1.2 1.3 1.3Pakistan Karachi 10,021 13,125 16,693 2.70 2.40 20.4 19.8 18.5Pakistan Lahore 5,449 7,132 9,150 2.69 2.49 11.1 10.8 10.1Pakistan Multan 1,263 1,659 2,174 2.73 2.70 2.6 2.5 2.4Pakistan Peshawar 1,066 1,422 1,868 2.88 2.73 2.2 2.1 2.1Pakistan Quetta 614 841 1,113 3.15 2.80 1.3 1.3 1.2Pakistan Rawalpindi 1,520 2,026 2,646 2.87 2.67 3.1 3.1 2.9Philippines Cebu 721 860 1,046 1.76 1.96 1.9 1.9 1.8Philippines Davao 1,152 1,519 1,881 2.77 2.14 3.1 3.3 3.3Philippines Manila 9,958 11,628 13,687 1.55 1.63 26.7 25.4 23.7Philippines Zamboanga 605 854 1,082 3.45 2.37 1.6 1.9 1.9Republic of Korea Goyang 744 961 1,025 2.56 0.64 2.0 2.4 2.4Republic of Korea Bucheon 763 909 960 1.75 0.55 2.1 2.3 2.3Republic of Korea Incheon 2,464 2,583 2,630 0.47 0.18 6.7 6.4 6.2Republic of Korea Gwangju 1,346 1,476 1,524 0.92 0.32 3.6 3.7 3.6Republic of Korea Busan 3,673 3,425 3,409 -0.70 -0.05 9.9 8.5 8.0Republic of Korea Seongnam 911 955 983 0.47 0.29 2.5 2.4 2.3Republic of Korea Seoul 9,917 9,773 9,767 -0.15 -0.01 26.8 24.3 23.1Republic of Korea Suweon 932 1,132 1,193 1.94 0.52 2.5 2.8 2.8Republic of Korea Daegu 2,478 2,458 2,481 -0.08 0.09 6.7 6.1 5.9Republic of Korea Daejon 1,362 1,509 1,562 1.02 0.35 3.7 3.8 3.7Republic of Korea Ulsan 1,011 1,081 1,116 0.67 0.32 2.7 2.7 2.6Saudi Arabia Al-Madinah (Medina) 795 1,104 1,351 3.28 2.02 4.8 5.1 5.1Saudi Arabia Ar-Riyadh (Riyadh) 3,567 4,848 5,809 3.07 1.81 21.5 22.5 21.8Saudi Arabia Ad-Dammam 639 902 1,109 3.45 2.07 3.8 4.2 4.2Saudi Arabia Jiddah 2,509 3,234 3,868 2.54 1.79 15.1 15.0 14.5Saudi Arabia Makkah (Mecca) 1,168 1,484 1,789 2.39 1.87 7.0 6.9 6.7Singapore Singapore 4,018 4,837 5,219 1.86 0.76 100.0 100.0 100.0Syrian Arab Republic Dimashq (Damascus) 2,063 2,597 3,213 2.30 2.13 24.1 20.7 20.1Syrian Arab Republic Halab (Aleppo) 2,204 3,087 3,864 3.37 2.25 25.7 24.6 24.2Syrian Arab Republic Hamah 495 897 1,180 5.96 2.74 5.8 7.2 7.4Syrian Arab Republic Hims (Homs) 856 1,328 1,702 4.39 2.48 10.0 10.6 10.7Thailand Krung Thep (Bangkok) 6,332 6,976 7,902 0.97 1.25 32.6 30.1 28.4Turkey Adana 1,123 1,361 1,556 1.92 1.34 2.6 2.6 2.5Turkey Ankara 3,179 3,906 4,401 2.06 1.19 7.4 7.4 7.1Turkey Antalya 595 838 969 3.42 1.45 1.4 1.6 1.6Turkey Bursa 1,180 1,588 1,816 2.97 1.34 2.7 3.0 2.9Turkey Gaziantep 844 1,109 1,274 2.73 1.39 2.0 2.1 2.1Turkey Istanbul 8,744 10,525 11,689 1.85 1.05 20.3 20.0 18.8Turkey Izmir 2,216 2,723 3,083 2.06 1.24 5.2 5.2 5.0Turkey Konya 734 978 1,125 2.87 1.40 1.7 1.9 1.8United Arab Emirates Dubayy (Dubai) 906 1,567 1,934 5.48 2.10 34.9 39.6 39.3Uzbekistan Tashkent 2,135 2,210 2,420 0.35 0.91 23.0 21.9 20.5Viet Nam Da Nang - CP 570 838 1,146 3.85 3.13 3.0 3.1 3.2Viet Nam Hai Phòng 1,704 1,970 2,432 1.45 2.11 8.8 7.3 6.7Viet Nam Hà Noi 1,631 2,814 4,056 5.45 3.66 8.5 10.4 11.2Viet Nam Thành Pho Ho Chí Minh (Ho Chi Minh City) 4,336 6,167 8,067 3.52 2.69 22.5 22.8 22.2Yemen Sana'a' 1,365 2,342 3,585 5.40 4.26 28.6 30.4 29.7EUROPEAustria Wien (Vienna) 1,549 1,706 1,779 0.97 0.42 29.4 30.1 29.6Belarus Minsk 1,700 1,852 1,917 0.86 0.34 24.2 25.9 26.6Belgium Antwerpen 925 965 984 0.42 0.19 9.3 9.3 9.1Belgium Bruxelles-Brussel 1,776 1,904 1,948 0.70 0.23 17.9 18.3 18.1Bulgaria Sofia 1,128 1,196 1,215 0.59 0.16 20.4 22.3 23.3Czech Republic Praha (Prague) 1,172 1,162 1,168 -0.09 0.05 15.5 15.2 14.7Denmark København (Copenhagen) 1,077 1,186 1,238 0.96 0.43 23.7 24.9 25.1Finland Helsinki 1,019 1,117 1,170 0.92 0.46 24.0 24.6 24.3France Bordeaux 763 838 899 0.94 0.70 1.7 1.6 1.5France Lille 1,004 1,033 1,092 0.28 0.56 2.2 1.9 1.9France Lyon 1,362 1,468 1,559 0.75 0.60 3.0 2.7 2.7France Marseille-Aix-en-Provence 1,363 1,469 1,560 0.75 0.60 3.0 2.8 2.7France Nice-Cannes 899 977 1,045 0.83 0.67 2.0 1.8 1.8France Paris 9,739 10,485 10,880 0.74 0.37 21.4 19.6 18.7France Toulouse 778 912 989 1.59 0.81 1.7 1.7 1.7Germany Berlin 3,384 3,450 3,498 0.19 0.14 5.6 5.7 5.8Germany Hamburg 1,710 1,786 1,825 0.43 0.22 2.9 2.9 3.0Germany Köln (Cologne) 963 1,001 1,018 0.39 0.17 1.6 1.7 1.7Germany München (Munich) 1,202 1,349 1,412 1.15 0.46 2.0 2.2 2.3Greece Athínai (Athens) 3,179 3,257 3,312 0.24 0.17 48.6 47.4 45.3Greece Thessaloniki 797 837 868 0.49 0.36 12.2 12.2 11.9Hungary Budapest 1,787 1,706 1,711 -0.46 0.03 27.1 25.1 24.4Ireland Dublin 989 1,099 1,261 1.05 1.38 44.0 38.7 37.4Italy Milano (Milan) 2,985 2,967 2,981 -0.06 0.05 7.8 7.2 7.0Italy Napoli (Naples) 2,232 2,276 2,293 0.20 0.07 5.8 5.5 5.4Italy Palermo 855 875 891 0.23 0.18 2.2 2.1 2.1Italy Roma (Rome) 3,385 3,362 3,376 -0.07 0.04 8.8 8.2 7.9Italy Torino (Turin) 1,694 1,665 1,679 -0.17 0.08 4.4 4.1 3.9Netherlands Amsterdam 1,005 1,049 1,097 0.43 0.45 8.2 7.6 7.4Netherlands Rotterdam 991 1,010 1,044 0.19 0.33 8.1 7.3 7.0Norway Oslo 774 888 985 1.37 1.04 22.7 23.0 22.9


TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

Poland Kraków (Cracow) 756 756 756 0.00 0.00 3.2 3.3 3.3Poland Warszawa (Warsaw) 1,666 1,712 1,722 0.27 0.06 7.0 7.4 7.4Portugal Lisboa (Lisbon) 2,672 2,824 2,973 0.55 0.51 48.0 43.3 41.6Portugal Porto 1,254 1,355 1,448 0.77 0.66 22.5 20.8 20.3Romania Bucuresti (Bucharest) 1,949 1,934 1,959 -0.08 0.13 16.6 15.9 15.3Russian Federation Chelyabinsk 1,082 1,094 1,095 0.11 0.01 1.0 1.1 1.1Russian Federation Yekaterinburg 1,303 1,344 1,376 0.31 0.24 1.2 1.3 1.4Russian Federation Kazan 1,096 1,140 1,164 0.39 0.21 1.0 1.1 1.2Russian Federation Krasnoyarsk 911 961 998 0.53 0.38 0.8 0.9 1.0Russian Federation Moskva (Moscow) 10,005 10,550 10,662 0.53 0.11 9.3 10.3 10.6Russian Federation Nizhniy Novgorod 1,331 1,267 1,253 -0.49 -0.11 1.2 1.2 1.2Russian Federation Novosibirsk 1,426 1,397 1,398 -0.21 0.01 1.3 1.4 1.4Russian Federation Omsk 1,136 1,124 1,112 -0.11 -0.11 1.1 1.1 1.1Russian Federation Perm 1,014 982 972 -0.32 -0.10 0.9 1.0 1.0Russian Federation Rostov-na-Donu (Rostov-on-Don) 1,061 1,046 1,038 -0.14 -0.08 1.0 1.0 1.0Russian Federation Samara 1,173 1,131 1,119 -0.36 -0.11 1.1 1.1 1.1Russian Federation Sankt Peterburg (Saint Petersburg) 4,719 4,575 4,557 -0.31 -0.04 4.4 4.5 4.5Russian Federation Saratov 878 822 798 -0.66 -0.30 0.8 0.8 0.8Russian Federation Ufa 1,049 1,023 1,016 -0.25 -0.07 1.0 1.0 1.0Russian Federation Volgograd 1,010 977 965 -0.33 -0.12 0.9 1.0 1.0Russian Federation Voronezh 854 842 838 -0.14 -0.05 0.8 0.8 0.8Serbia Beograd (Belgrade) 1,122 1,117 1,149 -0.04 0.28 20.9 20.2 19.6Spain Barcelona 4,560 5,083 5,443 1.09 0.68 14.9 14.5 14.1Spain Madrid 5,014 5,851 6,379 1.54 0.86 16.3 16.7 16.6Spain Valencia 795 814 857 0.24 0.51 2.6 2.3 2.2Sweden Stockholm 1,206 1,285 1,327 0.63 0.32 16.2 16.3 15.9Switzerland Zürich (Zurich) 1,078 1,150 1,196 0.65 0.39 20.5 20.6 20.2Ukraine Dnipropetrovs'k 1,077 1,004 967 -0.70 -0.38 3.3 3.2 3.1Ukraine Donets'k 1,026 966 941 -0.60 -0.26 3.1 3.1 3.0Ukraine Kharkiv 1,484 1,453 1,444 -0.21 -0.06 4.5 4.6 4.7Ukraine Kyiv (Kiev) 2,606 2,805 2,914 0.74 0.38 7.9 9.0 9.4Ukraine Odesa 1,037 1,009 1,011 -0.27 0.02 3.2 3.2 3.3Ukraine Zaporizhzhya 822 775 758 -0.59 -0.22 2.5 2.5 2.5United Kingdom Birmingham 2,285 2,302 2,375 0.07 0.31 4.9 4.7 4.5United Kingdom Glasgow 1,171 1,170 1,218 -0.01 0.40 2.5 2.4 2.3United Kingdom Liverpool 818 819 857 0.01 0.45 1.8 1.7 1.6United Kingdom London 8,225 8,631 8,753 0.48 0.14 17.8 17.5 16.5United Kingdom Manchester 2,248 2,253 2,325 0.02 0.31 4.9 4.6 4.4United Kingdom Newcastle upon Tyne 880 891 932 0.12 0.45 1.9 1.8 1.8United Kingdom West Yorkshire 1,495 1,547 1,606 0.34 0.37 3.2 3.1 3.0LATIN AMERICA AND THE CARIBBEANArgentina Buenos Aires 11,847 13,074 13,606 0.99 0.40 35.6 34.8 32.7Argentina Córdoba 1,348 1,493 1,601 1.02 0.70 4.0 4.0 3.9Argentina Mendoza 838 917 990 0.90 0.77 2.5 2.4 2.4Argentina Rosario 1,152 1,231 1,322 0.66 0.71 3.5 3.3 3.2Argentina San Miguel de Tucumán 722 831 899 1.41 0.79 2.2 2.2 2.2Bolivia La Paz 1,390 1,673 2,005 1.85 1.81 27.0 25.1 24.3Bolivia Santa Cruz 1,054 1,649 2,103 4.48 2.43 20.5 24.7 25.4Brazil Aracaju 606 782 883 2.55 1.21 0.4 0.5 0.5Brazil Baixada Santista1 1,468 1,819 2,014 2.14 1.02 1.0 1.1 1.1Brazil Belém 1,748 2,191 2,427 2.26 1.02 1.2 1.3 1.3Brazil Belo Horizonte 4,659 5,852 6,420 2.28 0.93 3.3 3.5 3.4Brazil Brasília 2,746 3,905 4,433 3.52 1.27 1.9 2.3 2.4Brazil Campinas 2,264 2,818 3,109 2.19 0.98 1.6 1.7 1.7Brazil Cuiabá 686 772 843 1.18 0.88 0.5 0.5 0.5Brazil Curitiba 2,494 3,462 3,913 3.28 1.22 1.8 2.0 2.1Brazil Florianópolis 734 1,049 1,210 3.57 1.43 0.5 0.6 0.6Brazil Fortaleza 2,875 3,719 4,130 2.57 1.05 2.0 2.2 2.2Brazil Goiânia 1,635 2,146 2,405 2.72 1.14 1.2 1.3 1.3Brazil Grande São Luís 1,066 1,283 1,415 1.85 0.98 0.8 0.8 0.8Brazil Grande Vitória 1,398 1,848 2,078 2.79 1.17 1.0 1.1 1.1Brazil João Pessoa 827 1,015 1,129 2.05 1.06 0.6 0.6 0.6Brazil Londrina 613 814 925 2.84 1.28 0.4 0.5 0.5Brazil Maceió 952 1,192 1,329 2.25 1.09 0.7 0.7 0.7Brazil Manaus 1,392 1,775 1,979 2.43 1.09 1.0 1.0 1.1Brazil Natal 910 1,316 1,519 3.69 1.43 0.6 0.8 0.8Brazil Norte/Nordeste Catarinense2 815 1,069 1,207 2.71 1.21 0.6 0.6 0.6Brazil Pôrto Alegre 3,505 4,092 4,428 1.55 0.79 2.5 2.4 2.4Brazil Recife 3,230 3,871 4,219 1.81 0.86 2.3 2.3 2.3Brazil Rio de Janeiro 10,803 11,950 12,617 1.01 0.54 7.6 7.1 6.7Brazil Salvador 2,968 3,918 4,370 2.78 1.09 2.1 2.3 2.3Brazil São Paulo 17,099 20,262 21,628 1.70 0.65 12.1 12.0 11.6Brazil Teresina 789 900 984 1.32 0.89 0.6 0.5 0.5Chile Santiago 5,275 5,952 6,408 1.21 0.74 39.8 39.0 37.8Chile Valparaíso 803 873 946 0.84 0.80 6.1 5.7 5.6Colombia Barranquilla 1,531 1,867 2,145 1.98 1.39 5.3 5.4 5.3Colombia Bucaramanga 855 1,092 1,303 2.45 1.77 3.0 3.1 3.2Colombia Cali 1,950 2,401 2,800 2.08 1.54 6.8 6.9 6.9Colombia Cartagena 737 962 1,158 2.66 1.85 2.6 2.8 2.8Colombia Medellín 632 774 910 2.03 1.62 2.2 2.2 2.2

237Data Tables

TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

Colombia Bogotá 6,356 8,500 10,129 2.91 1.75 22.2 24.5 24.8Costa Rica San José 1,032 1,461 1,799 3.48 2.08 44.5 48.9 49.4Cuba La Habana (Havana) 2,187 2,130 2,095 -0.26 -0.17 26.1 25.3 24.8Dominican Republic Santo Domingo 1,813 2,180 2,552 1.84 1.58 33.3 30.8 29.8Ecuador Guayaquil 2,077 2,690 3,153 2.59 1.59 28.0 29.2 28.3Ecuador Quito 1,357 1,846 2,188 3.08 1.70 18.3 20.0 19.6El Salvador San Salvador 1,248 1,565 1,789 2.26 1.34 35.6 39.3 39.0Guatemala Ciudad de Guatemala (Guatemala City) 908 1,104 1,481 1.95 2.94 17.9 15.5 15.0Haiti Port-au-Prince 1,693 2,143 2,868 2.36 2.91 55.0 40.4 38.0Honduras Tegucigalpa 793 1,028 1,339 2.60 2.64 28.0 26.2 25.4Mexico Aguascalientes 734 926 1,039 2.32 1.15 1.0 1.1 1.1Mexico Chihuahua 683 840 939 2.07 1.11 0.9 1.0 1.0Mexico Ciudad de México (Mexico City) 18,022 19,460 20,476 0.77 0.51 24.2 22.6 21.2Mexico Ciudad Juárez 1,225 1,394 1,528 1.29 0.92 1.6 1.6 1.6Mexico Culiacán 749 836 918 1.10 0.94 1.0 1.0 1.0Mexico Guadalajara 3,703 4,402 4,796 1.73 0.86 5.0 5.1 5.0Mexico Hermosillo 616 781 878 2.38 1.18 0.8 0.9 0.9Mexico León de los Aldamas 1,290 1,571 1,739 1.97 1.02 1.7 1.8 1.8Mexico Mérida 848 1,015 1,127 1.80 1.05 1.1 1.2 1.2Mexico Mexicali 770 934 1,040 1.93 1.07 1.0 1.1 1.1Mexico Monterrey 3,266 3,896 4,253 1.76 0.88 4.4 4.5 4.4Mexico Puebla 1,907 2,315 2,551 1.94 0.97 2.6 2.7 2.6Mexico Querétaro 795 1,031 1,160 2.60 1.18 1.1 1.2 1.2Mexico Saltillo 643 801 897 2.20 1.13 0.9 0.9 0.9Mexico San Luis Potosí 858 1,049 1,168 2.01 1.07 1.2 1.2 1.2Mexico Tampico 659 761 842 1.43 1.01 0.9 0.9 0.9Mexico Tijuana 1,287 1,664 1,861 2.57 1.12 1.7 1.9 1.9Mexico Toluca de Lerdo 1,417 1,582 1,725 1.10 0.87 1.9 1.8 1.8Mexico Torreón 1,014 1,199 1,325 1.68 1.00 1.4 1.4 1.4Nicaragua Managua 887 944 1,103 0.62 1.56 31.8 28.3 27.1Panama Ciudad de Panamá (Panama City) 1,072 1,378 1,652 2.51 1.81 55.2 52.5 51.1Paraguay Asunción 1,507 2,030 2,505 2.98 2.10 50.9 51.1 49.6Peru Arequipa 678 789 903 1.52 1.35 3.6 3.5 3.4Peru Lima 7,294 8,941 10,145 2.04 1.26 38.4 39.4 38.4Puerto Rico San Juan 2,237 2,743 2,763 2.04 0.07 61.9 69.5 67.2Uruguay Montevideo 1,605 1,635 1,653 0.19 0.11 52.9 52.4 50.6Venezuela (Bolivarian Republic of) Barquisimeto 946 1,180 1,350 2.21 1.35 4.3 4.4 4.3Venezuela (Bolivarian Republic of) Caracas 2,864 3,090 3,467 0.76 1.15 13.1 11.4 10.9Venezuela (Bolivarian Republic of) Maracaibo 1,724 2,192 2,488 2.40 1.27 7.9 8.1 7.8Venezuela (Bolivarian Republic of) Maracay 898 1,057 1,208 1.63 1.34 4.1 3.9 3.8Venezuela (Bolivarian Republic of) Valencia 1,392 1,770 2,014 2.40 1.29 6.3 6.5 6.3NORTHERN AMERICACanada Calgary 953 1,182 1,315 2.15 1.07 3.9 4.3 4.3Canada Edmonton 924 1,113 1,227 1.86 0.98 3.8 4.1 4.0Canada Montréal 3,471 3,783 4,048 0.86 0.68 14.2 13.9 13.3Canada Ottawa-Gatineau 1,079 1,182 1,285 0.91 0.84 4.4 4.3 4.2Canada Toronto 4,607 5,449 5,875 1.68 0.75 18.9 20.0 19.3Canada Vancouver 1,959 2,220 2,400 1.25 0.78 8.0 8.1 7.9United States of America Atlanta 3,542 4,691 5,036 2.81 0.71 1.6 1.8 1.7United States of America Austin 913 1,215 1,329 2.86 0.90 0.4 0.5 0.5United States of America Baltimore 2,083 2,320 2,508 1.08 0.78 0.9 0.9 0.9United States of America Boston 4,049 4,593 4,920 1.26 0.69 1.8 1.8 1.7United States of America Bridgeport-Stamford 894 1,055 1,154 1.66 0.90 0.4 0.4 0.4United States of America Buffalo 977 1,045 1,142 0.67 0.89 0.4 0.4 0.4United States of America Charlotte 769 1,043 1,144 3.05 0.92 0.3 0.4 0.4United States of America Chicago 8,333 9,204 9,758 0.99 0.58 3.7 3.5 3.3United States of America Cincinnati 1,508 1,686 1,831 1.12 0.83 0.7 0.6 0.6United States of America Cleveland 1,789 1,942 2,104 0.82 0.80 0.8 0.7 0.7United States of America Columbus, Ohio 1,138 1,313 1,432 1.43 0.87 0.5 0.5 0.5United States of America Dallas-Fort Worth 4,172 4,951 5,301 1.71 0.68 1.8 1.9 1.8United States of America Dayton 706 800 878 1.25 0.93 0.3 0.3 0.3United States of America Denver-Aurora 1,998 2,394 2,590 1.81 0.79 0.9 0.9 0.9United States of America Detroit 3,909 4,200 4,500 0.72 0.69 1.7 1.6 1.5United States of America El Paso 678 779 856 1.39 0.94 0.3 0.3 0.3United States of America Hartford 853 942 1,031 0.99 0.90 0.4 0.4 0.4United States of America Honolulu 720 812 891 1.20 0.93 0.3 0.3 0.3United States of America Houston 3,849 4,605 4,937 1.79 0.70 1.7 1.8 1.7United States of America Indianapolis 1,228 1,490 1,623 1.93 0.86 0.5 0.6 0.6United States of America Jacksonville, Florida 886 1,022 1,119 1.43 0.91 0.4 0.4 0.4United States of America Kansas City 1,365 1,513 1,645 1.03 0.84 0.6 0.6 0.6United States of America Las Vegas 1,335 1,916 2,086 3.61 0.85 0.6 0.7 0.7United States of America Los Angeles-Long Beach-Santa Ana 11,814 12,762 13,463 0.77 0.53 5.2 4.9 4.6United States of America Louisville 866 979 1,071 1.23 0.90 0.4 0.4 0.4United States of America McAllen 532 789 870 3.94 0.98 0.2 0.3 0.3United States of America Memphis 976 1,117 1,221 1.35 0.89 0.4 0.4 0.4United States of America Miami 4,946 5,750 6,142 1.51 0.66 2.2 2.2 2.1United States of America Milwaukee 1,311 1,428 1,554 0.85 0.85 0.6 0.5 0.5United States of America Minneapolis-St. Paul 2,397 2,693 2,905 1.16 0.76 1.1 1.0 1.0United States of America Nashville-Davidson 755 911 999 1.88 0.92 0.3 0.3 0.3United States of America New Orleans 1,009 858 984 -1.62 1.37 0.4 0.3 0.3United States of America New York-Newark 17,846 19,425 20,374 0.85 0.48 7.8 7.4 6.9


TABLE C.1 continued


2000 2010 2020 2000–2010 2010–2020 2000 2010 2020

United States of America Oklahoma City 748 812 891 0.82 0.93 0.3 0.3 0.3United States of America Orlando 1,165 1,400 1,526 1.84 0.86 0.5 0.5 0.5United States of America Philadelphia 5,160 5,626 6,004 0.86 0.65 2.3 2.2 2.0United States of America Phoenix-Mesa 2,934 3,684 3,965 2.28 0.74 1.3 1.4 1.3United States of America Pittsburgh 1,755 1,887 2,045 0.73 0.80 0.8 0.7 0.7United States of America Portland 1,595 1,944 2,110 1.98 0.82 0.7 0.7 0.7United States of America Providence 1,178 1,317 1,435 1.12 0.86 0.5 0.5 0.5United States of America Raleigh 549 769 848 3.37 0.97 0.2 0.3 0.3United States of America Richmond 822 944 1,034 1.38 0.91 0.4 0.4 0.4United States of America Riverside-San Bernardino 1,516 1,807 1,962 1.76 0.82 0.7 0.7 0.7United States of America Rochester 696 780 857 1.14 0.94 0.3 0.3 0.3United States of America Sacramento 1,402 1,660 1,805 1.69 0.84 0.6 0.6 0.6United States of America Salt Lake City 890 997 1,091 1.14 0.90 0.4 0.4 0.4United States of America San Antonio 1,333 1,521 1,655 1.32 0.84 0.6 0.6 0.6United States of America San Diego 2,683 2,999 3,231 1.11 0.75 1.2 1.1 1.1United States of America San Francisco-Oakland 3,236 3,541 3,804 0.90 0.72 1.4 1.4 1.3United States of America San Jose 1,543 1,718 1,865 1.07 0.82 0.7 0.7 0.6United States of America Seattle 2,727 3,171 3,415 1.51 0.74 1.2 1.2 1.2United States of America St. Louis 2,081 2,259 2,442 0.82 0.78 0.9 0.9 0.8United States of America Tampa-St Petersburg 2,072 2,387 2,581 1.42 0.78 0.9 0.9 0.9United States of America Tucson 724 853 936 1.64 0.93 0.3 0.3 0.3United States of America Virginia Beach 1,397 1,534 1,668 0.94 0.84 0.6 0.6 0.6United States of America Washington, DC 3,949 4,460 4,779 1.22 0.69 1.7 1.7 1.6OCEANIAAustralia Adelaide 1,102 1,168 1,263 0.58 0.78 6.6 6.1 5.9Australia Brisbane 1,603 1,970 2,178 2.06 1.00 9.6 10.3 10.1Australia Melbourne 3,433 3,853 4,152 1.15 0.75 20.5 20.1 19.3Australia Perth 1,373 1,599 1,753 1.52 0.92 8.2 8.3 8.2Australia Sydney 4,078 4,429 4,733 0.83 0.66 24.4 23.1 22.1New Zealand Auckland 1,063 1,404 1,631 2.79 1.50 32.1 37.9 40.2

Source: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York.

Notes:(1) Including Santos.(2) Including Jointville.

239Data Tables

TABLE C.2Population of Capital Cities (2009)

City population City population as a percentage of

Urban population Total population('000) (%) (%)

AFRICAAlgeria El Djazaïr (Algiers) 2,740 11.9 7.9Angola Luanda 4,511 42.3 24.4Benin1 Cotonou 815 21.9 9.1Botswana Gaborone 196 16.6 10.0Burkina Faso Ouagadougou 1,777 45.4 11.3Burundi Bujumbura 455 51.3 5.5Cameroon Yaoundé 1,739 15.5 8.9Cape Verde Praia 125 41.0 24.8Central African Republic Bangui 702 41.0 15.9Chad N'Djaména 808 26.6 7.2Comoros Moroni 49 25.6 7.2Congo Brazzaville 1,292 56.9 35.1Côte d’Ivoire2 Abidjan 4,009 38.2 19.0Côte d’Ivoire2 Yamoussoukro 808 7.7 3.8Democratic Republic of the Congo Kinshasa 8,401 36.8 12.7Djibouti Djibouti 567 86.1 65.6Egypt Al-Qahirah (Cairo) 10,903 30.3 13.1Equatorial Guinea Malabo 128 47.8 18.9Eritrea Asmara 649 60.6 12.8Ethiopia Addis Ababa 2,863 21.0 3.5Gabon Libreville 619 49.0 42.0Gambia Banjul 436 44.6 25.6Ghana Accra 2,269 18.8 9.5Guinea Conakry 1,597 45.5 15.9Guinea-Bissau Bissau 302 62.7 18.7Kenya Nairobi 3,375 38.8 8.5Lesotho Maseru 220 40.7 10.6Liberia Monrovia 882 47.0 22.3Libyan Arab Jamahiriya Tarabulus (Tripoli) 1,095 22.0 17.1Madagascar Antananarivo 1,816 31.0 9.3Malawi Lilongwe 821 27.9 5.4Mali Bamako 1,628 35.7 12.5Mauritania Nouakchott 709 52.3 21.5Mauritius Port Louis 149 27.7 11.6Mayotte Mamoudzou 6 6.2 3.1Morocco Rabat 1,770 9.6 5.5Mozambique Maputo 1,589 18.4 6.9Namibia Windhoek 342 42.1 15.7Niger Niamey 1,004 38.7 6.6Nigeria Abuja 1,857 2.4 1.2Réunion Saint-Denis 141 18.2 17.0Rwanda Kigali 909 49.0 9.1Saint Helena Jamestown 1 39.5 15.7São Tomé and Príncipe São Tomé 60 59.9 36.8Senegal Dakar 2,777 52.6 22.2Seychelles Victoria 26 56.3 30.9Sierra Leone Freetown 875 40.4 15.4Somalia Muqdisho (Mogadishu) 1,353 40.1 14.8South Africa3 Bloemfontein 436 1.4 0.9South Africa3 CapeTown 3,353 10.9 6.7South Africa3 Pretoria 1,404 4.6 2.8Sudan Al-Khartum (Khartoum) 5,021 30.2 11.9Swaziland4 Lobamba … … …Swaziland4 Mbabane 74 29.1 6.2Togo Lomé 1,593 56.3 24.1Tunisia Tunis 759 11.0 7.4Uganda Kampala 1,535 35.8 4.7United Republic of Tanzania Dodoma 200 1.8 0.5Western Sahara El Aaiún 213 50.9 41.5Zambia Lusaka 1,413 30.7 10.9Zimbabwe Harare 1,606 34.0 12.8ASIAAfghanistan Kabul 3,573 56.9 12.7Armenia Yerevan 1,110 56.1 36.0Azerbaijan Baku 1,950 42.6 22.1Bahrain Al-Manamah (Manama) 163 23.3 20.6Bangladesh Dhaka 14,251 31.9 8.8Bhutan Thimphu 89 37.8 12.8Brunei Darussalam Bandar Seri Begawan 22 7.4 5.6Cambodia Phnum Pénh (Phnom Penh) 1,519 51.8 10.3China Beijing 12,214 2.0 0.9China, Hong Kong SAR5 Hong Kong 7,022 100.0 100.0China, Macao SAR6 Macao 538 100.0 100.0Cyprus Lefkosia (Nicosia) 240 39.3 27.5Democratic People’s Republic of Korea P'yongyang 2,828 19.7 11.8Georgia Tbilisi 1,115 49.7 26.2India7 Delhi 21,720 6.1 1.8Indonesia Jakarta 9,121 9.0 4.0


TABLE C.2continued



Iran (Islamic Republic of) Tehran 7,190 13.8 9.7Iraq Baghdad 5,751 28.2 18.7Israel Jerusalem 768 11.7 10.7Japan Tokyo 36,507 43.1 28.7Jordan Amman 1,088 22.0 17.2Kazakhstan Astana 650 7.1 4.2Kuwait Al Kuwayt (Kuwait City) 2,230 75.9 74.7Kyrgyzstan Bishkek 854 45.0 15.6Lao People’s Democratic Republic Vientiane 799 39.5 12.6Lebanon Bayrut (Beirut) 1,909 51.9 45.2Malaysia8 Kuala Lumpur 1,494 7.6 5.4Maldives Male 120 100.0 38.9Mongolia Ulaanbaatar 949 57.7 35.5Myanmar Nay Pyi Taw 992 6.0 2.0Nepal Kathmandu 990 18.7 3.4Occupied Palestinian Territory Ramallah 69 2.2 1.6Oman Masqat (Muscat) 634 30.6 22.3Pakistan Islamabad 832 1.3 0.5Philippines Manila 11,449 25.6 12.4Qatar Ad-Dawhah (Doha) 427 31.6 30.3Republic of Korea Seoul 9,778 24.5 20.2Saudi Arabia Ar-Riyadh (Riyadh) 4,725 22.4 18.4Singapore Singapore 4,737 100.0 100.0Sri Lanka9 Colombo 681 23.5 3.4Sri Lanka9 Sri Jayewardenepura Kotte 123 4.2 0.6Syrian Arab Republic Dimashq (Damascus) 2,527 20.8 11.5Tajikistan Dushanbe 704 38.5 10.1Thailand Krung Thep (Bangkok) 6,902 30.3 10.2Timor-Leste Dili 166 53.0 14.7Turkey Ankara 3,846 7.4 5.1Turkmenistan Ashgabat 637 25.4 12.5United Arab Emirates Abu Zaby (Abu Dhabi) 666 17.3 14.5Uzbekistan Tashkent 2,201 22.1 8.0Viet Nam Hà Noi 2,668 10.2 3.0Yemen Sana'a' 2,229 30.3 9.5EUROPEAlbania Tiranë (Tirana) 433 26.9 13.7Andorra Andorra la Vella 25 32.9 29.1Austria Wien (Vienna) 1,693 30.1 20.2Belarus Minsk 1,837 25.7 19.1Belgium Bruxelles-Brussel 1,892 18.2 17.8Bosnia and Herzegovina Sarajevo 392 21.7 10.4Bulgaria Sofia 1,192 22.2 15.8Channel Islands10 St. Helier and St. Peter Port 30 63.4 19.8Croatia Zagreb 685 27.0 15.5Czech Republic Praha (Prague) 1,162 15.2 11.2Denmark København (Copenhagen) 1,174 24.8 21.5Estonia Tallinn 399 42.9 29.8Faeroe Islands Tórshavn 20 100.0 40.3Finland Helsinki 1,107 24.5 20.8France Paris 10,410 19.7 16.7Germany Berlin 3,438 5.7 4.2Gibraltar Gibraltar 31 100.0 100.0Greece Athínai (Athens) 3,252 47.6 29.1Holy See Vatican City 1 100.0 100.0Hungary Budapest 1,705 25.2 17.1Iceland Reykjavík 198 65.8 61.4Ireland Dublin 1,084 39.0 24.0Isle of Man Douglas 26 63.9 32.4Italy Roma (Rome) 3,357 8.2 5.6Latvia Riga 711 46.6 31.6Liechtenstein Vaduz 5 100.0 14.3Lithuania Vilnius 546 24.8 16.6Luxembourg Luxembourg-Ville 90 21.7 18.5Malta Valletta 199 51.6 48.8Monaco Monaco 33 100.0 100.0Montenegro Podgorica 144 37.5 23.0Netherlands11 Amsterdam 1,044 7.6 6.3Norway Oslo 875 23.0 18.2Poland Warszawa (Warsaw) 1,710 7.4 4.5Portugal Lisboa (Lisbon) 2,808 43.6 26.2Republic of Moldova Chisinau 650 39.0 18.0Romania Bucuresti (Bucharest) 1,933 16.0 9.1Russian Federation Moskva (Moscow) 10,523 10.2 7.5San Marino San Marino 4 14.9 14.0Serbia Beograd (Belgrade) 1,115 20.3 11.3Slovakia Bratislava 428 14.4 7.9Slovenia Ljubljana 260 26.0 12.9Spain Madrid 5,762 16.6 12.8

241Data Tables

TABLE C.2continued



Sweden Stockholm 1,279 16.3 13.8Switzerland Bern 346 6.2 4.6TFYR Macedonia12 Skopje 480 39.7 23.5Ukraine Kyiv (Kiev) 2,779 8.9 6.1United Kingdom London 8,615 17.6 14.0LATIN AMERICA AND THE CARIBBEANAnguilla The Valley 2 10.8 10.8Antigua and Barbuda St. John's 27 100.0 30.3Argentina Buenos Aires 12,988 35.0 32.2Aruba Oranjestad 33 66.4 31.1Bahamas Nassau 248 86.4 72.5Barbados Bridgetown 112 100.0 43.8Belize Belmopan 20 12.4 6.4Bolivia13 La Paz 1,642 25.2 16.6Bolivia13 Sucre 281 4.3 2.8Brazil Brasília 3,789 2.3 2.0British Virgin Islands Road Town 9 100.0 40.7Cayman Islands George Town 32 56.5 56.5Chile Santiago 5,883 39.1 34.7Colombia Bogotá 8,262 24.2 18.1Costa Rica San José 1,416 48.4 30.9Cuba La Habana (Havana) 2,140 25.4 19.1Dominica Roseau 14 31.9 21.4Dominican Republic Santo Domingo 2,138 30.9 21.2Ecuador Quito 1,801 19.9 13.2El Salvador San Salvador 1,534 39.0 24.9Falkland Islands (Malvinas) Stanley 2 100.0 73.1French Guiana Cayenne 62 36.3 27.7Grenada St. George's 40 100.0 38.9Guadeloupe Basse-Terre 13 2.9 2.8Guatemala Ciudad de Guatemala (Guatemala City) 1,075 15.6 7.7Guyana Georgetown 132 60.6 17.3Haiti Port-au-Prince 2,643 52.1 26.3Honduras Tegucigalpa 1,000 26.3 13.4Jamaica Kingston 580 41.0 21.3Martinique Fort-de-France 89 24.6 21.9Mexico Ciudad de México (Mexico City) 19,319 22.7 17.6Montserrat14 Brades Estate 1 98.7 13.9Montserrat14 Plymouth 0 0.1 0.0Netherlands Antilles Willemstad 123 67.0 62.2Nicaragua Managua 934 28.5 16.3Panama Ciudad de Panamá (Panama City) 1,346 52.6 39.0Paraguay Asunción 1,977 51.1 31.1Peru Lima 8,769 39.3 30.1Puerto Rico San Juan 2,730 69.5 68.6Saint Kitts and Nevis Basseterre 13 76.9 24.8Saint Lucia Castries 15 32.1 8.9Saint Vincent and the Grenadines Kingstown 28 52.8 25.8Suriname Paramaribo 259 72.4 49.9Trinidad and Tobago Port of Spain 57 31.7 4.3Turks and Caicos Islands Grand Turk 6 20.4 18.9United States Virgin Islands Charlotte Amalie 54 51.4 48.9Uruguay Montevideo 1,633 52.6 48.6Venezuela (Bolivarian Republic of) Caracas 3,051 11.5 10.7NORTHERN AMERICABermuda Hamilton 12 17.8 17.8Canada15 Ottawa-Gatineau 1,170 4.3 3.5Greenland Nuuk (Godthåb) 15 31.6 26.5Saint-Pierre-et-Miquelon Saint-Pierre 5 100.0 90.4United States of America Washington, DC 4,421 1.7 1.4OCEANIAAmerican Samoa Pago Pago 60 96.0 88.9Australia Canberra 384 2.0 1.8Cook Islands16 Rarotonga 15 100.0 74.5Fiji Greater Suva 174 39.8 20.5French Polynesia Papeete 133 96.0 49.4Guam Hagåtña 153 92.4 86.0Kiribati17 Tarawa 43 100.0 43.8Marshall Islands Majuro 30 66.8 47.7Micronesia (Fed. States of) Palikir 7 27.8 6.3Nauru Nauru 10 100.0 100.0New Caledonia Nouméa 144 100.0 57.4New Zealand Wellington 391 10.6 9.2Niue Alofi 1 100.0 37.0Northern Mariana Islands18 Saipan 79 100.0 91.2Palau Melekeok 1 5.9 4.9Papua New Guinea Port Moresby 314 37.3 4.7Pitcairn Adamstown 0 — 100.0Samoa Apia 36 100.0 20.4


TABLE C.2continued



Solomon Islands Honiara 72 75.5 13.7Tokelau19 .. .. ..Tonga Nuku'alofa 24 100.0 23.3Tuvalu Funafuti 5 100.0 49.9Vanuatu Port Vila 44 72.5 18.2Wallis and Futuna Islands Matu-Utu 1 — 6.5

Source: United Nations Department of Economic and Social Affairs, Population Division (2010) World Urbanization Prospects: The 2009 Revision, United Nations, New York.

Notes:(1) Porto-Novo is the constitutional capital, Cotonou is the seat of government.(2) Yamoussoukro is the capital, Abidjan is the seat of government.(3) Pretoria is the administrative capital, Cape Town is the legislative capital and Bloemfontein is the judicial capital.(4) Mbabane is the administrative capital, Lobamba is the legislative capital.(5) As of 1 July 1997, Hong Kong became a Special Administrative Region (SAR) of China.(6) As of 20 December 1999, Macao became a Special Administrative Region (SAR) of China.(7) The capital is New Delhi, included in the urban agglomeration of Delhi. The population of New Delhi was estimated at 294,783 in the year 2001.(8) Kuala Lumpur is the financial capital, Putrajaya is the administrative capital.(9) Colombo is the commercial capital, Sri Jayewardenepura Kotte is the administrative and legislative capital.(10) Refers to Guernsey and Jersey. St. Helier is the capital of the Bailiwick of Jersey and St. Peter Port is the capital of the Bailiwick of Guernsey.(11) Amsterdam is the capital, 's-Gravenhage is the seat of government.(12) The former Yugoslav Republic of Macedonia.(13) La Paz is the capital and the seat of government; Sucre is the legal capital and the seat of the judiciary.(14) Due to volcanic activity, Plymouth was abandoned in 1997. The government premises have been established at Brades Estate.(15) The capital is Ottawa.(16) The capital is Avarua, located on the island of Rarotonga; the estimated population refers to the island of Rarotonga. Population estimates for Avarua have not been made available.(17) The capital is Bairiki, located on the atoll of Tarawa; the estimated population refers to the island of South Tarawa. Population estimates for Bairiki have not been made available.(18) The capital is Garapan, located on the island of Saipan; the estimated population refers to the island of Saipan. The population of Garapan was estimated at 3,588 in the year 2000.(19) There is no capital in Tokelau. Each atoll (Atafu, Fakaofo and Nukunonu) has its own administrative centre.

243Data Tables

TABLE C.3Access to Services in Selected Cities

Percentage of households with access to

1990–19991 2000–20091

Survey Improved Piped Improved Sewer- Tele- Mobile(s)Connec- Survey Improved Piped Improved Sewer- Tele- Mobile(s)Connec-year water water sanitation age phone(s) tion to year water water sanitation age phone(s) tion to

electricity electricity

AFRICAAngola Luanda … … … … … … … 2006 51.4 36.6 92.4 53.2 88.2 40.1 75.5Benin Cotonou 1996 99.0 98.1 71.2 … … … 56.6 … … … … … … …Benin Djougou 1996 84.3 65.4 45.1 … … … 23.5 2006 90.6 62.6 51.9 … 3.9 31.0 47.4Benin Porto-Novo 1996 57.7 40.3 50.8 … … … 29.4 2006 77.0 64.1 68.4 … 8.1 57.3 66.9Burkina Faso Ouagadougou 1999 88.5 27.1 51.5 6.4 13.7 … 41.3 2006 83.3 39.4 56.5 4.6 17.3 62.8 61.6Cameroon Douala 1998 77.2 32.2 80.8 26.0 7.6 … 93.8 2006 99.2 51.0 79.9 25.3 5.3 76.2 98.9Cameroon Yaoundé 1998 93.7 59.9 81.9 22.0 11.5 … 96.3 2006 99.5 53.8 79.9 28.2 7.3 82.8 98.9Central African Republic Bangui 1994 74.9 9.9 49.5 5.5 5.8 … 15.3 2006 97.3 7.4 81.5 6.2 6.1 40.4 43.3Central African Republic Berbérati … … … … … … … 2006 94.7 3.5 79.7 0.7 2.7 13.1 4.1Central African Republic Boali … … … … … … … 2006 79.1 5.7 71.7 1.1 1.7 23.1 16.5Chad N'Djaména 1997 30.6 21.0 69.9 2.1 2.8 … 17.2 2004 87.8 27.6 65.4 10.3 6.5 … 29.2Comoros Fomboni … … … … … … … 2000 73.5 31.3 62.7 1.2 7.2 … 31.3Comoros Moroni 1996 95.7 22.2 67.6 11.4 13.0 … 55.1 2000 93.3 25.8 56.0 4.8 27.2 … 67.2Comoros Mutsamudu … … … … … … … 2000 96.9 73.6 51.8 8.0 10.1 … 53.1Congo Brazzaville … … … … … … … 2005 96.8 89.1 70.3 9.8 2.6 57.0 59.2Côte d'Ivoire Abidjan 1998 56.8 45.0 66.3 13.0 6.5 … 80.2 2005 98.6 83.3 79.3 42.7 49.5 0.0 95.0Democratic Republic of the Congo Kinshasa … … … … … … … 2007 92.3 45.8 80.8 29.6 0.6 74.8 82.0Democratic Republic of the Congo Lubumbashi … … … … … … … 2007 79.4 29.6 77.2 15.2 3.3 53.4 44.0Democratic Republic of the Congo Mbuji-Mayi … … … … … … … 2007 95.8 10.2 84.6 10.4 1.1 34.0 3.7Egypt Al-Iskandariyah (Alexandria)1995 99.7 94.2 79.4 61.0 … … 99.8 2008 100.0 99.4 99.9 99.9 61.4 61.9 99.8Egypt Al-Qahirah (Cairo) 1995 98.6 94.8 76.2 56.0 … … 99.0 2008 100.0 99.5 99.9 99.9 61.7 52.8 99.9Egypt Assiut 1995 94.7 91.7 61.8 27.1 … … 96.1 2008 100.0 98.0 99.4 99.1 58.2 46.3 100.0Egypt Aswan 1995 95.5 88.6 56.8 25.0 … … 98.2 2008 100.0 98.8 99.6 99.6 61.7 46.9 99.6Egypt Beni Suef 1995 88.9 83.8 57.6 28.3 … … 96.0 2008 100.0 86.6 97.8 97.3 50.0 48.4 100.0Egypt Damanhur 1995 99.3 98.7 77.6 65.8 … … 100.0 2008 100.0 100.0 100.0 100.0 58.5 48.1 100.0Egypt Damietta 1995 96.7 94.0 73.6 48.9 … … 97.8 2008 100.0 100.0 100.0 100.0 61.0 35.0 100.0Egypt Fayoum 1995 92.7 88.3 50.4 12.4 … … 97.8 2008 100.0 98.7 99.4 99.4 46.5 35.0 99.4Egypt Giza 1995 89.1 86.0 72.8 48.2 … … 98.4 2008 100.0 99.1 99.8 99.8 69.6 81.3 99.8Egypt Ismailia 1995 94.2 91.8 85.1 67.5 … … 99.1 2008 100.0 98.9 100.0 100.0 61.5 58.9 100.0Egypt Kafr El-Sheikh 1995 100.0 94.2 70.2 37.5 … … 99.0 2008 100.0 100.0 100.0 100.0 68.7 35.5 100.0Egypt Kharijah 1995 93.5 92.7 69.9 34.1 … … 99.2 2008 100.0 100.0 100.0 98.7 67.5 37.7 100.0Egypt Mansurah 1995 96.5 95.7 82.5 63.4 … … 99.6 2008 100.0 97.2 100.0 100.0 63.8 51.1 100.0Egypt Port Said 1995 98.7 96.5 90.1 82.4 … … 99.3 2008 98.4 98.2 100.0 100.0 69.3 49.7 100.0Egypt Qena 1995 89.9 81.4 68.2 37.2 … … 96.1 2008 100.0 96.8 100.0 99.5 59.9 47.1 100.0Egypt Sawhaj 1995 89.8 87.0 65.4 33.4 … … 96.0 2008 99.6 98.7 100.0 100.0 62.3 50.8 99.2Egypt Suez 1995 99.1 94.6 82.2 64.7 … … 99.3 2008 99.8 99.8 100.0 100.0 64.4 42.5 100.0Egypt Tahta 1995 99.2 90.8 75.6 48.3 … … 98.3 2008 99.7 88.7 100.0 100.0 59.9 49.8 100.0Ethiopia Addis Ababa … … … … … … … 2005 99.9 68.8 71.8 8.9 46.1 30.8 96.9Ethiopia Nazret … … … … … … … 2005 99.1 43.0 51.1 11.0 33.8 8.8 95.5Gabon Libreville … … … … … … … 2000 99.7 58.2 83.4 35.0 20.4 … 95.5Ghana Accra 1998 97.7 64.4 69.5 33.9 12.3 … 92.0 2008 60.1 37.3 93.8 37.1 11.1 89.5 90.8Guinea Conakry 1999 82.7 39.2 84.8 11.2 7.2 … 71.4 2005 96.4 45.2 80.3 11.1 28.9 … 94.5Kenya Mombasa 1998 73.9 30.0 61.3 29.2 7.4 … 47.5 2008 74.0 36.4 78.8 28.5 6.9 80.6 57.9Kenya Nairobi 1998 92.1 77.6 84.3 56.0 11.2 … 60.1 2008 98.3 78.2 93.6 71.3 9.4 92.5 88.6Lesotho Maseru … … … … … … … 2004 98.3 75.2 74.7 9.7 50.2 … 33.1Liberia Monrovia … … … … … … … 2007 81.6 8.4 51.9 34.4 … 70.8 8.1Madagascar Antananarivo 1997 80.1 24.8 52.9 14.4 3.6 … 55.7 2003 85.7 22.0 56.4 11.0 21.4 … 67.8Malawi Blantyre … … … … … … … 2006 97.0 30.6 42.6 10.9 6.7 35.1 32.7Malawi Lilongwe 1992 86.3 38.4 54.5 14.3 … … 18.5 2006 92.2 20.2 42.1 6.0 2.0 26.5 18.0Malawi Mzaza … … … … … … … 2006 96.7 41.9 42.1 17.0 5.5 32.5 35.6Mali Bamako 1996 70.5 17.3 51.6 4.3 3.7 … 33.7 2006 95.6 41.2 81.1 12.2 19.6 61.6 72.1Mauritania Nouakchott … … … … … … … 2001 94.4 27.8 58.2 4.8 7.2 … 47.2Morocco Dar-el-Beida (Casablanca) 1992 99.1 74.1 92.9 87.9 … … 78.7 2004 100.0 83.4 98.9 98.9 77.0 … 99.2Morocco Fès 1992 100.0 97.4 100.0 100.0 … … 100.0 2004 99.6 93.8 99.6 99.4 57.9 … 97.7Morocco Marrakech 1992 100.0 84.0 94.7 87.8 … … 90.4 2004 99.7 88.8 99.7 99.7 17.7 … 98.3Morocco Meknès 1992 99.2 89.4 99.2 99.2 … … 84.1 2004 99.2 85.6 97.0 97.0 68.4 … 97.3Morocco Rabat 1992 96.5 86.0 92.5 91.7 … … 83.9 2004 99.9 89.7 99.7 99.7 69.7 … 99.0Mozambique Maputo 1997 87.4 83.6 49.9 22.4 6.9 … 39.2 2003 82.8 66.4 48.8 8.0 5.2 … 28.8Namibia Windhoek 1992 98.0 93.9 92.7 90.2 … … 70.0 2007 98.6 82.8 87.1 86.0 37.1 … 83.4Niger Niamey 1998 63.5 33.2 47.7 5.0 4.1 … 51.0 2006 94.7 42.3 65.7 10.8 6.5 47.7 61.1Nigeria Akure 1999 94.1 … 58.8 … … … 76.5 2008 93.1 1.8 74.0 28.5 0.5 97.7 97.7Nigeria Damaturu 1999 61.5 23.1 71.8 15.4 2.6 … 64.1 2008 83.3 3.1 86.3 0.4 1.3 60.8 60.8Nigeria Effon Alaiye 1999 32.8 4.4 48.9 … 2.2 … 93.3 2008 80.0 7.3 61.1 26.2 1.7 93.2 93.2Nigeria Ibadan 1999 93.3 … 13.3 6.7 … … 33.3 2008 88.4 10.5 72.9 29.0 1.4 94.8 94.8Nigeria Kano 1999 54.8 27.3 58.8 10.7 4.5 … 82.2 2008 73.9 6.7 90.5 13.8 4.0 84.7 84.7Nigeria Lagos 1999 88.6 25.6 84.7 54.3 8.2 … 98.9 2008 94.0 5.4 91.6 56.3 7.4 98.0 98.0Nigeria Ogbomosho 1999 62.3 16.6 46.1 33.7 12.6 … 95.9 … … … … … … …Nigeria Owo 1999 34.4 7.4 68.8 24.4 9.9 … 95.3 … … … … … … …Nigeria Oyo 1999 35.0 11.0 65.8 39.6 3.6 … 92.1 … … … … … … …Nigeria Zaria 1999 74.4 54.6 55.8 15.1 4.6 … 94.2 2008 73.0 28.9 66.3 14.3 3.2 81.3 81.3Rwanda Kigali 1992 52.0 6.5 50.2 9.0 … … 36.0 2005 68.9 20.5 80.6 8.4 8.3 39.4 40.8Senegal Dakar 1997 95.5 77.8 70.8 42.4 20.4 … 80.2 2005 98.3 87.8 91.1 76.3 30.0 54.2 89.5South Africa Cape Town 1998 95.8 79.7 83.4 73.8 49.6 … 88.0 … … … … … … …South Africa Durban 1998 98.4 87.7 90.1 86.9 46.3 … 84.3 … … … … … … …South Africa Port Elizabeth 1998 97.2 66.8 68.5 55.7 27.0 … 63.3 … … … … … … …


TABLE C.3continued


1990–19991 2000–20091



South Africa Pretoria 1998 100.0 62.5 62.5 62.5 18.8 … 56.3 … … … … … … …South Africa West Rand 1998 99.4 84.2 84.8 84.8 47.6 … 75.0 … … … … … … …Swaziland Manzini … … … … … … … 2006 92.8 68.6 79.9 39.8 17.7 76.6 60.5Swaziland Mbabane … … … … … … … 2006 88.6 65.3 76.9 41.7 29.1 78.3 59.9Togo Lomé 1998 88.6 67.4 81.7 33.9 … … 51.2 2006 92.9 14.3 82.5 27.9 10.9 56.1 71.6United Republic of Tanzania Arusha 1999 97.8 23.7 39.6 … … … 5.9 2004 94.6 59.3 62.5 11.0 35.0 … 35.0United Republic of Tanzania Dar es Salaam 1999 90.1 78.8 51.9 3.2 … … 46.9 2004 81.1 62.1 55.6 10.0 43.4 … 59.8Uganda Kampala 1995 60.4 13.2 58.9 9.5 3.0 … 49.4 2006 92.6 26.0 100.0 10.7 5.4 67.6 59.0Zambia Chingola 1996 76.6 76.6 85.9 76.6 … … 78.1 2007 90.4 80.1 86.7 82.5 9.6 71.7 76.5Zambia Lusaka 1996 93.9 49.8 70.3 40.5 … … 50.7 2007 92.4 31.6 83.5 27.4 4.9 68.4 57.0Zambia Ndola 1996 92.3 59.4 85.1 69.3 … … 52.0 2007 74.1 39.5 64.5 34.0 8.1 57.8 38.9Zimbabwe Harare 1999 99.6 93.5 97.2 92.6 19.9 … 84.7 2005 99.2 92.7 98.4 87.1 17.5 37.6 86.3ASIAArmenia Armavir … … … … … … … 2005 98.7 96.2 98.0 83.8 80.2 35.2 100.0Armenia Artashat … … … … … … … 2005 100.0 83.8 94.6 87.4 77.9 23.8 99.8Armenia Gavar … … … … … … … 2005 99.3 88.7 99.6 77.3 82.9 21.7 99.8Armenia Gyumri … … … … … … … 2005 100.0 93.6 91.7 85.1 34.9 14.9 100.0Armenia Hrazdan … … … … … … … 2005 100.0 99.0 99.4 96.5 83.3 32.2 100.0Armenia Idjevan … … … … … … … 2005 99.1 91.5 98.7 73.2 86.3 13.4 100.0Armenia Kapan … … … … … … … 2005 100.0 100.0 99.8 97.9 88.9 16.2 100.0Armenia Vanadzor … … … … … … … 2005 99.4 96.8 98.5 84.5 76.5 18.7 99.7Armenia Yerevan … … … … … … … 2005 99.2 99.1 99.5 98.9 91.3 51.9 99.9Azerbaijan Baku … … … … … … … 2006 92.7 89.6 98.8 90.0 85.8 75.4 99.6Azerbaijan S· irvan … … … … … … … 2006 79.4 68.6 86.4 51.8 58.4 46.3 100.0Bangladesh Dhaka 1999 99.8 83.9 69.5 54.1 14.3 … 99.1 2007 100.0 63.2 55.1 42.5 9.7 64.0 96.9Bangladesh Rajshahi 1999 100.0 1.5 50.8 7.7 3.1 … 50.8 2007 100.0 0.8 53.4 18.0 1.1 31.9 60.1Cambodia Phnum Pénh (Phnom Penh) … … … … … … … 2005 96.7 86.0 92.4 91.7 … 86.1 96.1Cambodia Siem Réab … … … … … … … 2005 94.3 5.4 64.7 64.7 … 60.5 70.5India Agartala 1998 88.8 25.1 76.1 54.5 25.9 … 90.4 2006 95.1 35.1 86.3 50.0 25.5 18.0 91.8India Akola 1998 92.3 73.2 64.7 58.9 19.6 … 95.5 2006 99.2 69.8 61.4 60.9 21.3 24.6 93.1India Amritsar 1998 100.0 85.1 92.9 88.7 39.0 … 100.0 2006 100.0 79.0 98.7 95.4 26.6 40.3 97.0India Coimbatore 1998 94.1 36.0 90.0 89.1 19.1 … 89.6 2006 95.2 48.7 54.5 54.4 36.2 52.1 96.6India Hisar 1998 99.7 71.6 77.2 75.2 35.7 … 97.7 2006 99.2 65.3 77.4 70.3 25.5 38.1 97.9India Hyderabad 1998 98.4 87.5 70.3 51.5 29.7 … 96.1 2006 99.6 65.0 76.6 73.0 23.2 34.6 90.1India Jaipur 1998 98.5 83.7 91.5 91.0 28.5 … 98.0 2006 99.3 88.8 98.2 96.4 49.6 54.7 100.0India Jodhpur 1998 98.4 81.9 89.1 85.2 19.6 … 97.3 2006 97.9 84.7 69.2 66.1 34.7 38.4 94.7India Kanpur 1998 100.0 48.2 64.7 32.8 18.9 … 93.9 2006 98.6 37.4 81.3 68.2 19.1 39.1 92.6India Kharagpur 1998 90.9 40.4 87.1 81.0 15.0 … 82.6 2006 96.0 33.3 88.3 73.7 23.2 32.0 90.5India Kochi (Cochin) 1998 52.0 27.5 64.7 27.5 35.3 … 87.3 … … … … … … …India Kolkota 1998 98.5 35.1 94.3 89.5 25.6 … 93.8 2006 99.0 45.0 98.2 88.4 34.5 42.6 96.8India Krishnanagar 1998 89.7 32.7 78.6 73.9 18.9 … 81.5 2006 99.7 15.7 84.3 59.9 21.6 23.8 82.1India Mumbai (Bombay) 1998 99.4 76.7 98.0 97.8 31.6 … 99.0 2006 99.0 87.4 95.5 95.3 38.2 50.7 98.8India New Delhi 1998 99.2 80.8 94.0 90.2 45.4 … 97.6 2006 92.6 74.9 84.8 84.5 38.8 59.3 99.4India Pondichery 1998 93.7 35.9 52.5 45.1 13.0 … 87.0 2006 99.3 40.6 69.1 60.8 21.0 24.9 96.5India Pune (Poona) 1998 98.2 55.2 76.2 74.2 9.0 … 92.3 2006 99.1 74.0 78.7 75.9 23.3 35.5 97.0India Srinagar 1998 97.6 87.9 78.5 71.0 20.3 … 99.3 2006 98.8 83.5 64.1 60.0 41.6 55.2 99.4India Vijayawada 1998 96.9 39.2 68.1 60.3 13.2 … 96.8 2006 100.0 98.4 100.0 98.4 18.0 32.8 100.0India Yamunanagar 1998 99.7 59.7 77.7 70.6 27.0 … 98.3 2006 100.0 63.0 95.5 86.3 34.9 44.5 96.9Indonesia Bandung 1997 91.1 46.9 73.2 73.2 … … 100.0 2007 80.2 14.3 93.4 93.0 58.4 … 98.6Indonesia Bitung 1997 84.4 52.4 80.6 80.6 … … 96.3 … … … … … … …Indonesia Bogor 1997 95.1 42.0 89.6 89.6 … … 99.3 … … … … … … …Indonesia Denpasar 1997 98.6 53.6 92.1 92.1 … … 100.0 … … … … … … …Indonesia Dumai 1997 88.4 17.2 69.4 69.4 … … 85.8 … … … … … … …Indonesia Jakarta 1997 99.2 35.6 70.7 70.7 … … 99.9 2007 94.0 29.7 96.3 96.2 74.7 … 99.8Indonesia Jambi 1997 93.1 53.0 95.3 95.3 … … 98.7 … … … … … … …Indonesia Jaya Pura 1997 88.3 61.1 76.0 75.5 … … 88.0 … … … … … … …Indonesia Kediri 1997 94.1 17.9 48.0 47.7 … … 98.6 … … … … … … …Indonesia Medan 1997 99.1 68.0 90.0 90.0 … … 92.5 2007 83.5 48.6 93.2 91.0 67.0 … 99.6Indonesia Palembang 1997 98.0 81.2 90.8 90.8 … … 100.0 2007 79.2 16.8 87.6 85.7 57.8 … 95.6Indonesia Palu 1997 99.4 39.7 68.7 68.7 … … 92.1 … … … … … … …Indonesia Pekan Baru 1997 97.0 51.8 76.5 76.5 … … 97.9 … … … … … … …Indonesia Purwokerto 1997 100.0 48.6 72.1 72.1 … … 98.7 … … … … … … …Indonesia Surabaya 1997 100.0 71.0 70.5 70.5 … … 100.0 2007 86.9 16.2 82.3 80.3 56.8 … 99.3Indonesia Surakarta 1997 100.0 0.0 46.0 46.0 … … 100.0 2007 78.2 22.4 78.2 77.0 50.2 … 96.8Indonesia Ujung Pandang 1997 99.4 36.3 83.8 83.8 … … 98.4 2007 81.8 44.6 92.4 90.7 64.5 … 99.0Jordan Ajlun 1997 99.1 99.1 91.7 86.2 33.0 … 100.0 2007 97.5 69.5 99.8 39.6 30.3 89.5 99.3Jordan Al-Balqa 1997 98.6 98.1 97.7 95.3 35.8 … 99.1 2007 98.3 76.5 99.7 75.8 36.2 87.7 98.9Jordan Al-Karak 1997 97.1 96.6 92.6 81.7 33.7 … 98.9 2007 99.7 85.6 99.1 26.7 29.5 86.9 99.5Jordan Al-Mafraq 1997 97.7 96.9 99.2 96.1 44.5 … 98.4 2007 95.8 86.5 99.8 38.0 28.9 88.6 99.6Jordan Amman 1997 98.9 98.5 98.5 96.5 52.1 … 100.0 2007 98.8 67.0 99.9 81.2 45.3 91.4 98.6Jordan Aqaba 1997 100.0 100.0 98.9 98.3 45.5 … 100.0 2007 99.0 96.3 97.8 77.1 29.3 92.6 98.2Jordan At·-T·afı lah 1997 98.8 98.8 97.6 92.3 51.5 … 96.4 2007 99.6 97.3 99.9 29.9 31.5 90.8 99.0Jordan Az-Zarqa' 1997 99.2 99.1 99.6 99.1 29.5 … 100.0 2007 99.2 71.0 100.0 70.7 29.1 90.7 99.8Jordan Irbid 1997 92.1 90.6 95.2 91.8 28.2 … 99.6 2007 96.4 61.5 99.3 38.7 32.2 91.2 99.1Jordan Jarash 1997 91.8 87.8 94.9 89.8 27.6 … 100.0 2007 98.5 80.6 99.7 38.1 22.9 86.2 99.1Jordan Ma'an 1997 99.0 99.0 99.0 96.0 29.7 … 100.0 2007 97.6 76.4 99.8 32.5 25.0 93.2 99.1

245Data Tables

TABLE C.3continued


1990–19991 2000–20091



Jordan Ma'daba 1997 100.0 100.0 100.0 100.0 42.9 … 100.0 2007 97.8 82.7 100.0 66.3 28.5 89.6 98.6Kazakhstan Almaty 1999 97.0 94.3 87.6 77.9 78.1 … 99.7 2006 100.0 98.7 98.7 82.9 89.7 62.2 100.0Kazakhstan Ôskemen … … … … … … … 2006 99.4 81.2 100.0 54.0 62.3 33.4 99.8Kazakhstan Zezqazg·an 1999 100.0 100.0 100.0 100.0 75.5 … 100.0 … … … … … … …Kazakhstan Qaragandy … … … … … … … 2006 98.2 88.1 99.5 82.6 70.7 41.0 99.6Kazakhstan Symkent 1999 100.0 100.0 100.0 100.0 73.7 … 100.0 2006 92.6 83.0 100.0 39.4 54.9 37.5 100.0Kyrgyzstan Bishkek 1997 99.2 95.3 84.0 68.5 63.7 … 100.0 2006 100.0 96.0 99.8 68.4 72.1 54.8 99.8Pakistan Faisalabad 1990 98.1 78.1 87.6 87.2 … … 98.7 2006 95.4 59.4 80.0 79.7 67.4 … 98.7Pakistan Islamabad 1990 94.1 80.3 71.0 70.3 … … 97.8 2006 96.5 57.7 83.2 82.9 61.5 … 99.5Pakistan Karachi 1990 96.6 77.4 92.1 90.0 … … 96.8 2006 92.4 66.7 85.3 82.2 64.5 … 97.5Pakistan Quetta … … … … … … … 2006 97.6 79.3 76.5 72.0 62.7 … 98.8Philippines Bacolod 1998 92.7 31.1 75.0 71.3 12.8 … 78.7 2008 97.8 43.3 78.1 77.3 15.2 77.5 86.6Philippines Cagayan de Oro 1998 86.8 28.9 97.4 97.4 7.9 … 86.8 2008 100.0 16.1 98.9 78.7 14.9 78.5 93.3Philippines Cebu 1998 88.0 42.1 88.4 76.4 21.6 … 85.6 2008 99.0 21.9 84.4 80.3 22.4 80.6 93.4Philippines Manila 1998 91.0 65.9 96.9 92.3 45.7 … 98.7 2008 99.4 45.3 96.9 96.7 32.2 87.1 98.0Turkey Adana 1998 100.0 99.5 99.0 90.2 71.6 7.4 … 2004 99.5 92.2 99.6 90.4 76.8 39.0 …Turkey Aksaray 1998 47.6 42.9 64.3 21.4 69.0 7.1 … 2004 97.5 57.5 97.5 75.0 70.0 42.5 …Turkey Ankara 1998 97.4 86.6 99.5 99.0 90.3 23.6 … 2004 99.5 80.2 99.3 98.5 87.2 36.1 …Turkey Antalya 1998 91.7 89.1 90.1 19.8 83.3 20.3 … 2004 99.5 74.3 89.6 60.7 86.9 31.1 …Turkey Bursa 1998 92.0 87.7 98.8 89.5 82.7 14.8 … 2004 99.8 71.3 100.0 100.0 82.8 40.8 …Turkey Gaziantep 1998 96.2 94.9 90.4 89.7 73.1 7.7 … 2004 99.6 97.7 99.6 99.6 73.0 43.3 …Turkey Istanbul 1998 89.7 19.6 99.4 98.7 79.9 29.1 … 2004 99.3 39.7 99.1 95.9 83.3 35.6 …Turkey Izmir 1998 99.4 86.9 100.0 99.4 84.0 16.0 … 2004 98.3 56.1 100.0 99.7 84.5 39.5 …Turkey Karaman 1998 100.0 100.0 82.6 17.4 87.0 8.7 … … … … … … … …Turkey Kırıkkale 1998 94.7 63.2 100.0 100.0 94.7 15.8 … 2004 100.0 23.9 100.0 100.0 87.0 50.0 …Turkey Malatya 1998 98.3 98.3 100.0 100.0 75.9 8.6 … 2004 100.0 100.0 99.2 99.2 86.5 37.6 …Turkey Van 1998 95.8 95.8 93.8 62.5 62.5 4.2 … 2004 98.9 93.6 77.7 42.6 78.7 33.0 …Uzbekistan Tashkent 1996 99.4 98.7 89.4 81.0 64.5 … 100.0 … … … … … … …Viet Nam Da Nang - CP … … … … … … … 2002 88.8 88.8 100.0 100.0 80.0 … 100.0Viet Nam Hà Noi 1997 77.1 50.6 90.8 60.1 41.8 … 100.0 2002 77.2 74.1 97.3 95.8 72.9 … 100.0Viet Nam Hai Phòng 1997 97.9 75.1 72.1 61.2 6.4 … 100.0 2002 98.2 95.5 96.0 90.0 39.0 … 100.0Viet Nam Thành Pho Ho Chí Minh 1997 90.6 89.4 95.8 92.7 40.0 … 99.7 2002 89.3 88.8 98.4 96.6 74.5 … 99.8

(Ho Chi Minh City)Yemen Aden 1991 97.0 97.0 91.4 88.2 28.7 … 95.6 … … … … … … …Yemen Sana'a' 1991 93.9 93.5 60.9 58.5 38.6 … 98.8 2006 56.8 22.5 88.7 48.8 … … …Yemen Taiz 1991 85.6 85.6 55.9 48.9 26.1 … 95.2 … … … … … … …EUROPEMoldova Chisinau … … … … … … … 2005 99.5 89.1 97.8 91.9 93.6 60.6 99.7Ukraine Ce·rkasy … … … … … … … 2007 99.4 81.5 99.7 56.6 64.4 79.8 99.7Ukraine Ce·rnihiv … … … … … … … 2007 100.0 73.9 76.0 46.5 81.7 60.9 100.0Ukraine Ce·rnivcy … … … … … … … 2007 100.0 94.9 97.0 86.9 87.2 61.8 100.0Ukraine Che·rson … … … … … … … 2007 99.7 78.0 100.0 62.1 54.4 71.3 100.0Ukraine Chme· l'nyckyj … … … … … … … 2007 98.1 81.5 98.4 81.7 84.5 64.2 99.4Ukraine Dnipropetrovs'k … … … … … … … 2007 100.0 91.5 100.0 77.4 71.1 69.9 100.0Ukraine Donets'k … … … … … … … 2007 100.0 76.4 99.8 65.6 50.3 79.3 99.9Ukraine Ivano-Frankivs'k … … … … … … … 2007 100.0 72.6 100.0 72.7 85.6 77.5 100.0Ukraine Kharkiv … … … … … … … 2007 100.0 79.0 99.7 69.9 68.8 70.9 100.0Ukraine Kirovhrad … … … … … … … 2007 99.7 65.0 99.6 46.6 53.5 76.4 100.0Ukraine Krym … … … … … … … 2007 99.6 91.3 99.3 68.5 58.2 68.9 99.8Ukraine Kyïv … … … … … … … 2007 99.8 99.4 99.8 99.8 94.4 85.6 99.8Ukraine Luhans'k … … … … … … … 2007 99.1 39.6 98.9 69.4 61.0 72.8 100.0Ukraine L'viv … … … … … … … 2007 100.0 89.7 99.8 90.4 73.6 78.1 100.0Ukraine Mykolaïv … … … … … … … 2007 93.2 91.0 100.0 80.5 47.2 56.2 99.6Ukraine Odesa … … … … … … … 2007 99.8 85.8 99.3 63.1 72.5 61.7 99.9Ukraine Poltava … … … … … … … 2007 98.3 71.7 100.0 74.8 70.9 71.1 100.0Ukraine Rivne· … … … … … … … 2007 100.0 95.0 98.0 76.6 72.6 72.4 99.3Ukraine Se·vastopol' … … … … … … … 2007 100.0 95.4 100.0 92.5 85.9 65.5 100.0Ukraine Sumy … … … … … … … 2007 99.6 78.9 100.0 63.9 70.6 70.2 100.0Ukraine Te·rnopil' … … … … … … … 2007 97.7 84.2 100.0 67.3 82.5 73.5 100.0Ukraine Uzhorod … … … … … … … 2007 95.2 80.8 95.3 67.5 58.3 80.1 100.0Ukraine Vinnycja … … … … … … … 2007 94.7 66.8 99.7 63.2 65.6 74.8 100.0Ukraine Volyn' … … … … … … … 2007 100.0 84.3 100.0 69.3 85.3 71.0 100.0Ukraine Zaporizhzhya … … … … … … … 2007 100.0 99.2 100.0 77.7 70.4 76.4 100.0Ukraine Zytomyr … … … … … … … 2007 100.0 48.0 98.9 53.9 66.9 69.0 99.6LATIN AMERICA AND THE CARIBBEANBelize Belize … … … … … … … 2006 99.6 24.1 96.1 95.0 49.3 70.5 98.3Bolivia Cobija 1998 88.5 88.5 78.7 52.5 45.9 … 88.5 2008 86.7 85.2 79.7 64.5 23.4 85.0 96.2Bolivia Cochabamba 1998 83.5 83.5 65.0 44.3 47.5 7.6 98.2 2008 84.4 83.0 83.7 75.1 42.6 74.0 98.2Bolivia La Paz 1998 95.3 95.3 55.1 39.3 33.5 8.1 97.2 2008 97.5 95.0 83.6 78.1 29.7 77.0 98.3Bolivia Oruro 1998 93.9 93.9 42.3 32.2 29.5 4.8 95.8 2008 97.2 92.4 70.2 69.0 43.1 70.6 96.4Bolivia Potosí 1998 96.7 96.7 48.9 23.9 25.7 3.2 95.6 2008 98.1 95.1 82.8 81.5 23.7 74.9 97.8Bolivia Santa Cruz 1998 96.7 96.7 75.0 56.0 36.9 10.7 95.9 2008 98.9 98.1 78.3 59.9 25.8 84.5 97.7Bolivia Sucre 1998 96.5 96.5 71.9 61.4 36.1 8.4 95.7 2008 94.4 88.6 77.2 76.9 31.5 66.5 97.2Bolivia Tarija 1998 99.3 99.3 79.7 68.3 41.2 6.6 94.5 2008 99.3 94.5 86.4 79.8 31.7 81.8 94.9Bolivia Trinidad 1998 69.8 69.8 59.0 25.8 22.8 2.6 84.0 2008 65.0 60.7 65.4 42.4 14.9 65.8 91.5Brazil Belo Horizonte 1996 90.9 84.4 91.3 87.6 … … 100.0 … … … … … … …


TABLE C.3continued


1990–19991 2000–20091



Brazil Brasília 1996 90.2 89.8 81.7 71.2 … … 99.6 … … … … … … …Brazil Curitiba 1996 90.0 84.2 88.7 78.7 … … 100.0 … … … … … … …Brazil Fortaleza 1996 82.4 76.8 59.8 35.9 … … 97.2 … … … … … … …Brazil Goiânia 1996 95.7 93.4 84.8 75.7 … … 98.3 … … … … … … …Brazil Rio de Janeiro 1996 89.4 88.5 83.1 79.4 … … 99.6 … … … … … … …Brazil São Paulo 1996 98.2 93.8 90.3 87.6 … … 99.6 … … … … … … …Brazil Victoria 1996 94.6 90.4 90.8 87.5 … … 99.2 … … … … … … …Colombia Armenia 1995 100.0 100.0 99.3 98.9 55.4 … 99.3 2005 99.7 96.8 99.8 99.8 69.7 … 98.1Colombia Barranquilla 1995 95.1 93.9 94.6 80.4 23.5 … 99.8 2005 95.9 86.8 96.0 94.8 45.4 … 99.6Colombia Bogotá 1995 100.0 100.0 99.8 99.7 80.6 … 99.9 2005 99.6 96.4 99.9 99.9 81.7 … 99.6Colombia Bucaramanga 1995 100.0 100.0 97.2 96.7 42.4 … 100.0 2005 98.6 95.3 97.3 97.3 76.3 … 99.8Colombia Cali 1995 99.9 99.7 97.3 96.7 43.1 … 99.9 2005 99.6 97.7 99.0 99.0 71.4 … 99.8Colombia Cartagena 1995 98.4 93.6 88.0 74.2 27.1 … 99.6 2005 94.9 83.0 92.8 91.4 49.2 … 99.7Colombia Cúcuta 1995 98.3 98.3 97.7 96.4 27.2 … 100.0 2005 99.5 95.8 97.4 97.1 57.0 … 99.6Colombia Ibagué 1995 99.1 99.1 97.0 93.0 32.5 … 97.7 2005 99.3 98.0 99.7 99.7 62.8 … 99.1Colombia Manizales 1995 99.6 99.6 99.6 99.6 52.3 … 98.8 2005 99.6 99.6 99.8 99.8 72.4 … 99.5Colombia Medellín 1995 99.4 99.4 96.5 96.3 52.3 … 98.8 2005 99.1 91.2 99.4 99.4 81.8 … 99.1Colombia Montería 1995 86.9 79.3 71.2 47.9 21.7 … 93.1 2005 74.2 59.9 93.9 92.7 53.1 … 98.4Colombia Neiva 1995 99.6 99.6 97.2 96.6 43.9 … 97.4 2005 99.1 98.7 98.6 98.3 64.4 … 98.1Colombia Pereira 1995 100.0 100.0 100.0 100.0 57.0 … 98.9 2005 100.0 98.1 99.6 99.6 72.9 … 99.4Colombia Popayán 1995 100.0 100.0 98.6 98.6 54.9 … 100.0 2005 98.9 83.1 97.0 96.7 63.3 … 97.2Colombia Quibdó 1995 94.3 64.0 8.2 1.7 35.1 … 79.6 2005 96.4 53.2 85.9 85.7 55.9 … 98.2Colombia Ríohacha 1995 100.0 100.0 92.9 89.3 16.8 … 94.6 2005 95.8 63.9 96.7 96.3 50.5 … 98.9Colombia Santa Marta 1995 80.0 74.2 79.6 67.2 18.4 … 100.0 2005 96.4 78.5 94.0 93.0 49.3 … 98.7Colombia Sincelejo 1995 100.0 100.0 86.6 73.5 19.5 … 98.5 2005 97.5 86.0 94.1 93.6 53.1 … 98.7Colombia Tunja 1995 100.0 100.0 99.3 98.7 22.1 … 98.7 2005 99.2 90.8 99.1 99.1 60.8 … 99.5Colombia Valledupar 1995 100.0 100.0 99.2 97.4 14.8 … 99.4 2005 95.3 90.6 90.3 90.2 43.3 … 97.4Colombia Villavicencio 1995 96.4 96.4 100.0 100.0 34.0 … 99.2 2005 98.6 69.1 99.2 99.0 64.9 … 98.9Dominican Republic Azua 1996 97.8 75.1 89.0 46.4 22.7 … … 2007 92.1 49.1 92.5 43.2 15.3 46.5 99.1Dominican Republic Baní 1996 100.0 83.7 97.8 70.7 34.8 … … 2007 78.4 22.6 93.6 60.0 29.4 64.6 98.7Dominican Republic Barahona 1996 92.2 89.3 79.7 33.1 14.8 … … 2007 85.9 57.3 86.9 47.1 18.7 52.4 98.7Dominican Republic Bonao 1996 97.7 90.7 93.0 62.8 46.5 … … 2007 94.6 34.3 98.3 82.2 31.4 75.2 99.2Dominican Republic Cotuí 1996 99.1 80.0 85.2 36.5 7.8 … … 2007 93.7 6.5 93.5 74.4 29.4 69.7 100.0Dominican Republic Dajabón 1996 100.0 96.7 93.3 23.3 17.8 … … 2007 82.2 38.3 94.7 49.9 18.5 62.5 96.9Dominican Republic Hato Mayor del Rey … … … … … … … 2007 88.0 3.0 95.1 59.1 18.7 73.9 98.0Dominican Republic Higüey 1996 100.0 12.1 97.0 59.1 34.8 … … 2007 94.3 0.1 97.8 74.4 21.7 79.2 98.0Dominican Republic La Romana 1996 100.0 29.3 92.9 52.2 34.2 … … 2007 88.7 6.9 92.6 66.9 17.0 74.5 98.6Dominican Republic La Vega 1996 98.8 54.7 98.8 94.2 59.3 … … 2007 91.5 27.6 96.7 78.9 26.0 73.1 98.6Dominican Republic Mao 1996 98.9 80.7 94.8 33.0 23.6 … … 2007 96.4 36.6 95.1 46.9 24.0 72.9 96.1Dominican Republic Moca 1996 97.5 65.8 97.5 74.7 59.5 … … 2007 97.9 37.9 97.1 74.0 23.6 73.6 98.2Dominican Republic Monte Cristi 1996 54.5 22.4 92.5 15.7 27.6 … … 2007 93.8 20.2 94.3 43.5 28.2 67.6 95.3Dominican Republic Monte Plata 1996 98.4 63.2 89.3 40.3 14.2 … … 2007 79.7 3.3 92.7 44.9 15.5 63.4 96.6Dominican Republic Nagua 1996 100.0 43.1 100.0 41.4 27.6 … … 2007 89.2 4.6 93.5 62.6 21.3 76.9 98.9Dominican Republic Neiba 1996 96.6 92.7 82.0 12.4 12.4 … … 2007 81.8 45.1 81.3 41.5 19.7 57.2 96.8Dominican Republic Puerto Plata 1996 97.4 46.2 98.7 66.7 32.1 … … 2007 95.3 10.2 97.0 87.6 30.7 78.2 97.9Dominican Republic Sabaneta 1996 100.0 79.1 96.5 51.2 27.9 … … 2007 89.6 21.2 93.3 56.1 27.3 73.7 98.7Dominican Republic Samaná 1996 96.6 82.8 51.7 24.1 3.4 … … 2007 92.4 9.7 89.6 68.9 17.6 76.2 97.0Dominican Republic San Cristóbal 1996 88.2 56.6 91.5 59.0 36.8 … … 2007 72.9 11.4 96.2 80.0 33.7 77.0 99.4Dominican Republic San Francisco de Macorís 1996 99.4 43.0 95.0 55.9 30.7 … … 2007 90.2 10.7 95.0 73.2 31.5 73.5 98.7Dominican Republic San Juan 1996 97.8 87.8 92.8 34.8 21.0 … … 2007 95.6 53.3 89.7 55.8 20.4 62.4 99.3Dominican Republic San Pedro de Macorís 1996 99.4 17.3 92.9 56.5 36.3 … … 2007 76.8 4.4 92.7 65.4 19.5 70.3 98.3Dominican Republic Santiago 1996 99.7 77.8 96.3 74.4 46.0 … … 2007 98.4 31.2 98.9 89.5 41.7 81.6 99.2Dominican Republic Santo Domingo 1999 97.7 31.1 87.2 74.6 54.3 … … 2007 80.9 9.0 96.0 85.2 39.0 79.3 98.6Guatemala Ciudad de Guatemala 1998 91.1 53.2 83.6 71.6 31.9 … 91.7 … … … … … … …

(Guatemala City)Guatemala Escuintla 1998 94.0 56.8 96.7 90.2 29.5 … 97.8 … … … … … … …Guatemala Quetzaltenango 1998 93.7 71.2 82.5 70.0 31.3 … 91.2 … … … … … … …Haiti Port-au-Prince 1994 48.5 31.9 93.4 16.9 … … 92.3 2006 78.6 25.4 57.6 17.3 11.2 48.6 88.0Honduras Choluteca … … … … … … … 2005 99.1 38.8 76.0 53.3 51.8 41.5 …Honduras Comayagua … … … … … … … 2005 94.6 30.3 87.6 75.0 38.1 47.5 …Honduras Juticalpa … … … … … … … 2005 96.9 35.2 78.2 52.9 46.2 43.3 …Honduras La Ceiba … … … … … … … 2005 94.1 35.9 91.3 73.5 29.9 64.3 …Honduras San Pedro Sula … … … … … … … 2005 98.9 30.2 93.3 84.0 40.1 57.6 …Honduras Santa Bárbara … … … … … … … 2005 91.6 48.3 78.7 61.8 16.4 34.2 …Honduras Santa Rosa de Copán … … … … … … … 2005 88.9 17.1 87.0 74.1 33.1 45.8 …Honduras Tegucigalpa … … … … … … … 2005 89.4 32.7 86.0 72.4 54.9 53.0 …Honduras Trujillo … … … … … … … 2005 91.8 24.8 92.7 71.6 45.7 51.8 …Honduras Yoro … … … … … … … 2005 97.4 30.1 91.7 72.8 44.2 54.6 …Honduras Yuscarán … … … … … … … 2005 92.6 42.4 83.4 58.8 35.1 37.2 …Nicaragua Chinandega 1998 82.1 78.6 62.2 25.9 8.2 … 84.0 2001 100.0 85.5 65.7 22.3 9.3 8.9 89.5Nicaragua Estelí 1998 95.3 94.5 66.7 36.5 12.5 … 84.9 2001 99.1 93.4 69.1 30.7 14.0 0.9 91.7Nicaragua Granada 1998 97.2 97.0 67.0 37.4 16.9 … 93.6 2001 99.8 97.4 71.6 35.8 23.9 12.3 95.0Nicaragua León 1998 92.4 92.0 68.8 40.5 12.6 … 92.5 2001 99.8 97.0 73.9 46.2 11.8 11.1 98.4Nicaragua Managua 1998 97.5 97.5 78.2 58.4 21.9 … 96.9 2001 99.8 97.1 81.7 61.1 29.1 21.9 99.6Nicaragua Masaya 1998 96.2 95.8 65.0 30.3 14.8 … 94.9 2001 100.0 98.9 69.4 31.6 18.4 10.4 97.9Nicaragua Matagalpa 1998 95.9 95.3 68.1 37.2 13.2 … 90.9 2001 98.1 87.5 72.0 30.2 16.5 1.2 92.2

247Data Tables

TABLE C.3continued


1990–19991 2000–20091



Peru Arequipa 1996 88.5 74.3 80.7 67.7 25.1 … 94.8 2004 93.6 93.2 89.5 84.6 36.1 … 98.1Peru Chiclayo 1996 89.1 74.8 72.1 55.0 20.6 … 88.7 2004 91.8 91.2 86.5 79.6 32.0 … 92.3Peru Chimbote 1996 76.4 72.0 79.6 68.4 24.0 … 91.4 2004 87.8 87.8 76.8 73.9 31.6 … 85.2Peru Lima 1996 83.1 73.7 85.1 77.1 35.7 … 97.4 2004 96.6 96.6 96.5 94.3 61.9 … 99.1Peru Piura 1996 88.9 84.8 78.9 67.4 18.9 … 83.4 2004 94.0 64.9 60.5 37.7 24.0 … 91.1Peru Tacna 1996 96.1 81.4 83.3 80.9 33.0 … 92.4 2004 100.0 100.0 98.6 97.7 27.9 … 99.0Peru Trujillo 1996 84.9 72.6 72.8 61.5 19.8 … 84.9 2004 93.5 93.5 98.3 96.0 50.7 … 98.1

Source: United Nations Human Settlements Programme (UN-Habitat), Global Urban Indicators Database 2010.

Notes:(1) Data are from the latest year availble in the period shown.

REFERENCES

A101 (2006) ‘Moscow will have a new suburb’,MASSHTAB, www.a101.ru/en/news.xml?&news_id=77&year_id=57&month_id=76, last accessed 18 October 2010

ABI (Association of British Insurers) (2005) FinancialRisks of Climate Change, Association of BritishInsurers, London, UK

ACIA (Arctic Climate Impact Assessment) (2004) ArcticClimate Impact Assessment, Cambridge UniversityPress, Cambridge, UK

ActionAid International (2006) Unjust Waters, ClimateChange, Flooding and the Protection of Poor AfricanCommunities: Experiences from Six African Cities,Actionaid International, www.reliefweb.int/rw/lib.nsf/db900sid/TBRL-76GR49/$file/Actionaid-UnjustWaters-Aug2007.pdf?openelement,last accessed 7 December 2010

Adams, J. (2007) ‘Rising sea levels threaten small Pacificisland nations’, New York Times, 3 May,www.nytimes.com/2007/05/03/world/asia/03iht-pacific.2.5548184.html? r=1, last accessed 20 January 2011

ADB (Asian Development Bank) (2005) Climate Proofing:A Risk-Based Approach to Adaptation, Pacific StudiesSeries, Manila

ADB (undated) ‘Clean energy financing partnership facility’, www.adb.org/Clean-Energy/cefpf.asp, lastaccessed 6 October 2010

Adelekan, I. O. (2010) ‘Vulnerability of poor urbancoastal communities to flooding in Lagos, Nigeria’,Environment and Urbanization 22(2): 433–450

Adeyinka S. O. and O. J. Taiwo (2006) ‘Lagos shorelinechange pattern: 1986–2002’, American-EurasianJournal of Scientific Research 1(1): 25–30

Adger, W. N. (1999) ‘Social vulnerability to climatechange and extremes in coastal Vietnam’, WorldDevelopment 27(2): 249–269

Adger, W. N. (2000) ‘Social and ecological resilience: Arethey related?’ Progress in Human Geography 24(3):347–364

Adger, W. N. (2001) ‘Scales of governance and environ-mental justice for adaptation and mitigation ofclimate change’, Journal of International Development13(7): 921–931

Adger, W. N., T. Hughes, C. Folke, S. Carpenter and J.Rockström (2005) ‘Social-ecological resilience tocoastal disasters’, Science 309(5737): 1036–1039

Adger, W. N., S. Agrawala, M. M. Q. Mirza, C. Conde, K.O’Brien, J. Pulhin, R. Pulwarty, B. Smit and K.Takahashi (2007) ‘Assessment of adaptation practices,options, constraints and capacity’, in M. L. Parry, O.F. Canziani, J. P. Palutikof, P. J. van der Linden and C.E. Hanson (eds) Climate Change 2007: Impacts,Adaptation and Vulnerability. Contribution of WorkingGroup II to the Fourth Assessment Report of the

Intergovernmental Panel on Climate Change,Cambridge University Press, Cambridge, UK,pp717–743

African Development Bank, Asian Development Bank,Department for International Development, EuropeanCommission, Federal Ministry for EconomicCooperation and Development-Germany,Development Cooperation-The Netherlands,Organisation for Economic Co-operation andDevelopment, United Nations DevelopmentProgramme, United Nations Environment Programmeand the World Bank (2003) Poverty and ClimateChange: Reducing the Vulnerability of the Poorthrough Adaptation, Washington, DC

Agencianova (2009) ‘El gobierno bonaerense inicia laconstrucción de viviendas bioclimáticas’,www.novacolombia.info/nota.asp?n=2009_6_9&id=9226&id_tiponota=10, last accessed 14 October2010

Agnew, M. and D. Viner (2001) ‘Potential impacts ofclimate change on international tourism’, Tourism andHospitality Research 3(1): 37–60

Ahern, M., R. S. Kovats, P. Wilkinson, R. Few and F.Matthies (2005) ‘Global health impacts of floods:Epidemiologic evidence’, Epidemiology Review 27(1):36–46

Akbari, H. (2005) Energy Saving Potentials and AirQuality Benefits of Urban Heat Island Mitigation,Lawrence Berkeley National Laboratory, Berkeley, CA

Akinbami, J. F. and A. Lawal (2009) ‘Opportunities andchallenges to electrical energy conservation and CO2emissions reduction in Nigeria’s building sector’,Paper prepared for the Fifth Urban ResearchSymposium, Cities and Climate Change: Respondingto an Urgent Agenda, 28–30 June, Marseille, France

Alam, M. and M. Rabbani (2007) ‘Vulnerabilities andresponses to climate change for Dhaka’, Environmentand Urbanization 19(1): 81–97

Alber, G. (2010) Gender, Cities and Climate Change,Unpublished thematic report prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Alber G. and K. Kern (2008) ‘Governing climate changein cities: Modes of urban climate governance inmulti-level systems’, OECD International Conference,Competitive Cities and Climate Change, 2nd AnnualMeeting of the OECD Roundtable Strategy for UrbanDevelopment, 9–10 October, Milan, Italy,www.oecd.org/dataoecd/22/7/41449602.pdf, lastaccessed 28 October 2010

Alberti, M. and L. R. Hutyra (2009) ‘Detecting carbonsignatures of development patterns across a gradientof urbanization: Linking observations, models, andscenarios’, Paper prepared for the Fifth UrbanResearch Symposium, Cities and Climate Change:

Responding to an Urgent Agenda, 28–30 June,Marseille, France

Aldy, J. E., S. Barrett and R. N. Stavins (2003) ‘Thirteenplus one: a comparison of global climate policy archi-tectures’, Climate Policy 3(4): 373–397

AlertNet (2010a) ‘UN Adaptation Fund gives green lightto first four projects’, www.alertnet.org/db/an_art/60167/2010/05/17-221110-1.htm

AlertNet (2010b) ‘Climate change: Adaptation Fundswings into action’, www.alertnet.org/thenews/newsdesk/IRIN/690db58da46ba960d48e0c009e677716.htm

Allman, L., P. Fleming and A. Wallace (2004) ‘Theprogress of English and Welsh local authorities inaddressing climate change’, Local Environment 9(3):271–283

Alston, L. J., G. D. Libecap and B. Mueller (2001) ‘Landreform policies, sources of conflict and implicationsfor de-forestation in the Brazilian Amazon’, Nota DiLavoro, 70.2001, Fonazione Eni Enrico Mattei, Milan,Italy

Ammann C. M., F. Joos, D. Schimel, B. L. Otto-Bliesnerand R. Tomas (2007) ‘Solar influence on climateduring the past millennium: Results from transientsimulations with the NCAR Climate System Model’,Proceedings of the National Academy of Sciences104(10): 3713–3718

Ananthapadmanabhan, G., K. Srinivas and V. Gopal(2007) Hiding Behind the Poor: A Report byGreenpeace on Climate Injustice, New Delhi, India

Andrews, C. (2008) ‘Greenhouse gas emissions alongthe rural–urban gradient’, Journal of EnvironmentalPlanning and Management 51(6): 847–870

Angel, S., S. Sheppard and D. Civco (2005) TheDynamics of Global Urban Expansion, Transport andUrban Development Department, World Bank,Washington, DC

Arup (2008) Zero Net Emissions by 2020 Update,Melbourne, City of Melbourne, Australia

Asia-Pacific Partnership on Clean Development andClimate (undated) ‘Frequently asked questions’,www.asiapacificpartnership.org/english/faq.aspx#FAQ1, last accessed 6 October 2010

Atteridge, A., C. K. Siebert, R. J. Klein, C. Butler and P.Tella (2009) ‘Bilateral finance institutions and climatechange: A mapping of climate portfolios’, StockholmEnvironment Institute for the Climate ChangeWorking Group for Bilateral Finance InstitutionsWorking Paper, Stockholm Environment Institute,Stockholm, Sweden, www. sei-international.org/mediamanager/documents/Publications/Climate-mitigation-adaptation/bilateral-finance-institutions-climate-change.pdf, last accessed 6 October 2010

Awuor, C. B., V. A. Orindi and A. O. Adwera (2008)‘Climate change and coastal cities: The case ofMombasa, Kenya’, Environment and Urbanization20(1): 231–242

Ayers, J. (2009) ‘International funding to support urbanadaptation to climate change’, Environment andUrbanization 21(1): 225–240

Ayers, J. and S. Huq (2009) ‘The value of linking mitiga-tion and adaptation: A case study of Bangladesh’,Environmental Management 43(5): 753–764

Aylett, A. (2010) ‘Changing perceptions of climatemitigation among competing priorities: The case ofDurban, South Africa’, Unpublished case studyprepared for the Global Report on Human Settlements2011, www.unhabitat.org/grhs/2011

Bai, X. (2007) ‘Industrial ecology and the global impactsof cities’, Journal of Industrial Ecology 11(2): 1–6

Baldasano, J., C. Soriano and L. Boada (1999) ‘Emission

inventory for greenhouse gases in the City ofBarcelona, 1987–1996’, Atmospheric Environment33(23): 3765–3775

Balk, D., M. R. Montgomery, G. McGranahan, D. Kim, V.Mara, M. Todd, T. Buettner and A. Dorelién (2009)‘Mapping urban settlements and the risks of climatechange in Africa, Asia and South America’, in J. M.Guzman, G. Martine, G. McGranahan, D. Schensuland C. Tacoli (eds) Population Dynamics and ClimateChange, United Nations Population Fund (UNFPA)and International Institute for Environment andDevelopment (IIED), London, pp80–103

Bangkok Metropolitan Administration (2009) Bangkok:Assessment Report on Climate Change 2009, GreenLeaf Foundation, Bangkok MetropolitanAdministration and United Nations EnvironmentProgramme Regional Office for Asia and the Pacific,Bangkok, Thailand

Banister, D., S. Watson and C. Wood (1997) ‘Sustainablecities: Transport, energy, and urban form’,Environment and Planning B: Planning and Design24(1): 125–143

Banks, N. (2008) ‘A tale of two wards: Political participa-tion and the urban poor in Dhaka city’, Environmentand Urbanization 20(2): 361–376

Barker T., I. Bashmakov, L. Bernstein, J. E. Bogner, P. R.Bosch, R. Dave, O. R. Davidson, B. S. Fisher, S.Gupta, K. Halsnæs, G. J. Heij, S. Kahn Ribeiro, S.Kobayashi, M. D. Levine, D. L. Martino, O. Masera, B.Metz, L. A. Meyer, G.-J. Nabuurs, A. Najam, N.Nakicenovic, H.-H. Rogner, J. Roy, J. Sathaye, R.Schock, P. Shukla, R. E. H. Sims, P. Smith, D. A.Tirpak, D. Urge-Vorsatz and D. Zhou (2007)‘Technical summary’, in B. Metz, O. R. Davidson, P. R.Bosch, R. Dave and L. A. Meyer (eds) Climate Change2007: Mitigation, Contribution of Working Group IIIto the Fourth Assessment Report of theIntergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork, pp25–93, www.ipcc.ch/pdf/assessment-report/ar4/wg3/ar4-wg3-ts.pdf, last accessed 11 October2010

Barry, E. J. (1943) Solar Water Heater, USP Office, USBartlett, S. (2008) ‘Climate change and children: Impacts

and implications for adaptation in low- to middle-income countries’, Environment and Urbanization20(2): 501–519

Bartlett, S., D. Dodman, J. Hardoy, D. Satterthwaite andC. Tacoli (2009) ‘Social aspects of climate change inurban areas in low- and middle-income nations’, Paperprepared for the Fifth Urban Research Symposium,Cities and Climate Change: Responding to an UrgentAgenda, 28–30 June, Marseille, France

Bastianoni, S., F. Pulselli and E. Tiezzi (2004) ‘Theproblem of assigning responsibility for greenhousegas emissions’, Ecological Economics 49(3): 253–257

Basu, R. and J. Samet (2002) ‘Relation between elevatedambient temperature and mortality: A review of theepidemiologic evidence’, Epidemiologic Reviews24(2): 190–202

Bates, B. C., Z. W. Kundzewicz, S. Wu and J. P. Palutikof(eds) (2008) ‘Climate change and water’, TechnicalPaper of the Intergovernmental Panel on ClimateChange, IPCC Secretariat, Geneva, Switzerland

Baumert, K., T. Herzog and J. Pershing (2005) Navigatingthe Numbers: Greenhouse Gas Data and InternationalClimate Policy, World Resources Institute,Washington, DC

BBC News (2010a) ‘Floods in north-east Brazil killdozens of people’, 23 June 2010, www.bbc.co.uk/news/10372362, last accessed 29 October 2010


BBC News (2010b) ‘Pakistan flood death toll “passes1,100”’, BBC News South Asia, www.bbc.co.uk/news/world-south-asia-10832166, last accessed 29 October 2010

BCIL (Biodiversity Conservation India Limited) (2009) T-Zed Case-Study, Unpublished report presented toUNEP, Bangalore

Beauchemin, C. and P. Bocquier (2004) ‘Migration andurbanization in Francophone West Africa: Anoverview of the recent empirical evidence’, UrbanStudies 41(11): 2245–2272

Beccherle, J. and J. Tirole (2010) ‘Regional initiatives andthe cost of delaying binding climate changeagreements’, www.idei.fr/doc/by/tirole/regionalinitiativesmay17.pdf, last accessed 7 October2010

Beniston, M. and H. Diaz (2004) ‘The 2003 heat wave asan example of summers in a greenhouse climate?Observations and climate model simulations forBasel, Switzerland’, Global and Planetary Change44(1–4): 73–81

Benson, C. and E. Clay (2004) ‘Beyond the damage:Probing the economic and financial consequences ofnatural disasters’, Presentation at OverseasDevelopment Institute (ODI), London, 11 May 2004

Berger, L. R. and D. Mohan (1996) Injury Control: AGlobal View, Oxford University Press, New Delhi,India

Bertaud, A., B. Lefevre and B. Yuen (2009) ‘GHGemissions, urban mobility and efficiency of urbanmorphology: A hypothesis’, Paper prepared for theFifth Urban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Betsill, M. M. (2001) ‘Mitigating climate change in USCities: Opportunities and obstacles’, LocalEnvironment 6(4): 393–406

Betsill, M. M. and H. Bulkeley (2007) ‘Looking back andthinking ahead: A decade of cities and climate changeresearch’, Local Environment 12(5): 447–456

Bicknell, J., D. Dodman and D. Satterthwaite (eds)(2009) Adapting Cities to Climate Change:Understanding and Addressing the DevelopmentChallenges, Earthscan, London

Biermann, F. and P. Pattberg (2008) ‘Global environmen-tal governance: Taking stock, moving forward’,Annual Review of Environment and Resources 33(1):277–294

Biermann, F., P. Pattberg, H. van Asselt and F. Zelli (2008)‘Fragmentation of global governance architectures:Case of climate policy’, Paper presented at the 49thInternational Studies Association’s (ISA’s) AnnualConvention, Bridging Multiple Divides, San Francisco,California, March 2008

Biermann, F., M. M. Betsill, J. Gupta, N. Kanie, L.Lebel, D. Liverman, H. Schroeder and B.Siebenhuner (2009) Earth System Governance –People, Places, and the Planet, Science andImplementation of the Earth System GovernanceProject, Earth System Governance Report 1,International Human Dimensions Programme, TheEarth System Governance Project, Bonn, Germany

Bigio, A. (2009) ‘Adapting to climate change andpreparing for natural disasters in the coastal cities ofNorth Africa’, Paper presented at the UrbanResearch Symposium, Cities and Climate Change:Responding to an Urgent Agenda, June 28–30,Marseilles, France

Bin, S. and R. Harris (2006) ‘The role of CO2embodiment in U.S.–China trade’, Energy Policy34(18): 4063–4068

Bird, N. and L. Peskett (2008) ‘Recent bilateral initiativesfor climate financing: Are they moving in the rightdirection?’, Opinion Paper No 112, OverseasDevelopment Institute (ODI), London,www.odi.org.uk/resources/download/2402.pdf, lastaccessed 6 October 2010

Bizikova L., T. Neale and I. Burton (2008) CanadianCommunities’ Guidebook for Adaptation to ClimateChange, Environment Canada and University ofBritish Columbia, Vancouver, Canada

Bloomberg, M. and R. Aggarwala (2008) ‘Think locally,act globally: How curbing global warming emissionscan improve local public health’, American Journal ofPreventative Medicine 35(5): 414–423

Boardman, B. (2007) ‘Examining the carbon agenda viathe 40% house scenario’, Building Research &Information 35(4): 363–378

Bodansky, D. (2001) ‘The history of the global climatechange regime’, in U. Luterbacher and D. F. Sprinz(eds) International Relations and Global ClimateChange, MIT Press Cambridge, MA, pp23–40

Boland, J. (1997) ‘Assessing urban water use and the roleof water conservation measures under climate uncer-tainty’, Climatic Change 37(1): 157–176

Boonyabancha, S. (2005) ‘Baan Mankong: Going to scalewith “slum” and squatter upgrading in Thailand’,Environment and Urbanization 17(1): 21–46

Boonyabancha, S. (2009) ‘Land for housing the poor bythe poor: Experiences from the Baan Mankongnationwide slum upgrading programme in Thailand’,Environment and Urbanization 21(2): 309–330

Boruff, B. J., C. Emrich and S. L. Cutter (2005) ‘Erosionhazard vulnerability of US coastal counties’, Journal ofCoastal Research 21(5): 932–942

Brasseur, G., K. Jacobs, E. Barron, R. Benedick, W.Chameides, T. Dietz, P. Romero Lankao, M.McFarland, H. Mooney, D. Nathan, E. Parson and R.Richels (2007) Analysis of Global ChangeAssessments: Lessons Learned, National AcademiesPress, Washington, DC

Breman, J., M. S. Alilio and A. Mills (2004) ‘Conqueringthe intolerable burden of malaria: What’s new, what’sneeded: A summary’, American Journal of TropicalMedicine and Hygiene 71(2), Supplement: 1–15

Brookings Institution (2009) Protecting and PromotingRights in Natural Disasters in South Asia: Preventionand Response, Report on the Project on InternalDisplacement, Chennai, India

Brown, M. and F. Southworth (2008) ‘Mitigating climatechange through green buildings and smart growth’,Environment and Planning A 40(3): 653–675

Brown, M. A., F. Southworth and A. Sarzynksi (2008)Shrinking the Carbon Footprint of MetropolitanAmerica, Brookings Institute, Washington, DC

Brown, O. (2007) ‘Climate change and forced migration:Observations, projections and implications’, HumanDevelopment Report Office Occasional Paper,2007/17, UNDP, http://hdr.undp.org/en/reports/global/hdr2007-2008/papers/brown_oli.pdf, lastaccessed 14 October 2010

Bulkeley, H. (2000) ‘Down to Earth: Local governmentand greenhouse policy in Australia’, AustralianGeographer 31: 289–308

Bulkeley, H. and M. Betsill (2003) Cities and ClimateChange: Urban Sustainability and GlobalEnvironmental Governance, Routledge, London

Bulkeley, H. and K. Kern (2006) ‘Local government andthe governing of climate change in Germany and theUK’, Urban Studies 43(12): 2237–2259

Bulkeley, H. and P. Newell (2010) Governing ClimateChange, Routledge, London, NY

251References

Bulkeley, H. and H. Schroeder (2008) ‘Governing climatechange post-2012: The role of global cities – London’,Working Paper No 123, Tyndall Centre for ClimateChange Research, www.tyndall.ac.uk/sites/default/files/wp123.pdf, last accessed 7 October 2010

Bulkeley, H., H. Schroeder, K. Janda, J. Zhao, A.Armstrong, S. Y. Chu and S. Ghosh (2009) ‘Cities andclimate change: The role of institutions, governanceand urban planning’, Paper prepared for the FifthUrban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Bull-Kamanga, L., K. Diagne, A. Lavell, F. Lerise, H.MacGregor, A. Maskrey, M. Meshack, M. Pelling, H.Reid, D. Satterthwaite, J. Songsore, K. Westgate andA. Yitambe (2003) ‘From everyday hazards to disas-ters: The accumulation of disaster risk in urbanareas’, Environment and Urbanization 15(1):193–204

Bumpus A. and D. Liverman (2008) ‘Accumulation bydecarbonisation and the governance of carbonoffsets’, Economic Geography 84(2): 127–155

Bundesministerium für Umwelt, Naturschutz undReaktorsicherheit (undated) KWK: Modellstadt Berlin,www.kwk-modellstadt-berlin.de/, last accessed 14October 2010

Burdett, R., T. Travers, D. Czischke, P. Rode and B. Moser(2005) Density and Urban Neighbourhoods inLondon, Enterprise LSE Cities, London

Burke, L., S. J. Brown and N. Christidis (2006)‘Modelling the recent evolution of global drought andprojections for the 21st century with the HadleyCenter climate model’, Journal of Hydrometeorology7(5): 1113–1125

C40 Cities (undated) ‘Participating cities’,www.c40cities.org/cities, last accessed 6 October 2010

Cabannes, Y. (2004) ‘Participatory budgeting: A signifi-cant contribution to participatory democracy’,Environment and Urbanization 16(1): 27–46

California Solutions for Global Warming (undated)‘California global warming solutions act’,www.solutionsforglobalwarming.org/1calpolicyAB32.html, last accessed 6 October 2010

Camilleri, M., R. Jaques and N. Isaacs (2001) ‘Impacts ofclimate change on building performance in NewZealand’, Building Research and Information 29(6):440–450

Campbell-Lendrum, D. and C. Corvalan (2007) ‘Climatechange and developing country cities: Implicationsfor environmental health and equity’, Journal ofUrban Health 84(1): 109–117

CAN (Climate Action Network International) (undated)‘Climate action network’, www.climatenetwork.org/,last accessed 7 October 2010

Capello, R., P. Nijkamp and G. Pepping (1999)Sustainable Cities and Energy Policies, Springer-Verlag,Berlin

Carmin, J. and Y. Zhang (2009) Achieving Urban ClimateAdaptation in Europe and Central Asia, World BankPolicy Research Working Paper 5088, World Bank,Washington, DC

Carmin, J., D. Roberts and I. Anguelovski (2009)‘Planning climate resilient cities: Early lessons fromearly adapters’, Paper prepared for the Fifth UrbanResearch Symposium, Cities and Climate Change:Responding to an Urgent Agenda, 28–30 June,Marseille, France

Casaubon, M. E., M. D. Peralta and A. M. Ponce de León(2008) Mexico City Climate Action Program2008–2012: Summary, Secretaría del MedioAmbiente del Distrito Federal Plaza de la

Constitución, Colonia Centro, www.sma.df.gob.mx/sma/links/download/archivos/paccm_summary.pdf,last accessed 12 October 2010

Castán Broto, V., P. Tabbush, K. Burningham, L. Elghaliand D. Edwards (2007) ‘Coal ash and risk: Four socialinterpretations of a pollution landscape’, LandscapeResearch 32: 481–497

Castán Broto, V., C. Carter and L. Elghali (2009) ‘Thegovernance of coal ash pollution in post-socialisttimes: power and expectations’, EnvironmentalPolitics 18(2): 279–286

CD4CDM (Capacity Development for CDM) (undated)‘CDM/JI Pipeline overview page’,http://cdmpipeline.org/overview.htm, last accessed 6October 2010

Centre for Clean Air Policy (undated) ‘Urban leadersadaptation initiative’, www.ccap.org/index.php?component=programs&id=6, last accessed 6 October 2010

CFCB (Carbon Finance Capacity Building Programme)(undated) ‘Carbon finance capacity buildingprogramme’, www.lowcarboncities.info/home.html,last accessed 6 October 2010

Choi, O. and A. Fisher (2003) ‘The impacts of socio-economic development and climate change on severeweather catastrophe losses: Mid-Atlantic Region(MAR) and the U.S.’, Climate Change 58(1–2):149–170

Church, J., N. White, R. Coleman, K. Lambeck and J.Mitrovica (2004) ‘Estimates of the regional distribu-tion of sea level rise over the 1950–2000 period’,American Meteorological Society 17(13): 2609–2625

CISDL (Centre for International SustainableDevelopment Law) (2002) ‘The principle of commonbut differentiated responsibilities: Origins and scope’,www.cisdl.org/pdf/brief_common.pdf, last accessed12 October 2010

City of Cape Town (2005) City of Cape Town ClimateChange Strategy, City of Cape Town

City of Cape Town (2006) Cape Town Energy and ClimateChange Strategy, Environmental Planning Department,City of Cape Town; www.capetown.gov.za/en/EnvironmentalResourceManagement/publications/Documents/Energy_+_Climate_Change_Strategy_2_-_10_2007_301020079335_465.pdf, lastaccessed 12 October 2010

City of Cape Town (2007) State of Energy Report for theCity of Cape Town 2007, Palmer Development Group,Cape Town, www.capetown.gov.za/en/EnvironmentalResourceManagement/publications/Documents/StateOfEnergy_Report_2007_v2.pdf, lastaccessed 12 October 2010

City of Cape Town (2010) ‘Cape Town prepares forwinter storms’, www.capetown.gov.za/en/Pages/CapeTownpreparesforwinterstorms.aspx, lastaccessed 14 October 2010

City of Cape Town (undated) Cape Town 2007–2012,Five Year Plan, Summary of the IntegratedDevelopment Plan (2007–2012), www.capetown.gov.za/en/IDP/Documents/idp/IDP_English.pdf, lastaccessed 14 October 2010

City of Melbourne (2009) City of Melbourne ClimateChange Adaptation Strategy, www.melbourne.vic.gov.au/AboutCouncil/PlansandPublications/strategies/Documents/climate_change_adaptation_strategy.PDF,last accessed 14 October 2010

City of New York (2007) Inventory of New York CityGreenhouse Gas Emissions, www.nyc.gov/html/planyc2030/downloads/pdf/emissions_inventory.pdf,last accessed 12 October 2010


City of New York (2009) Inventory of New York CityGreenhouse Gas Emissions, Updated 24 February2009, www.nyc.gov/html/planyc2030/html/downloads/download.shtml, last accessed 12 October2010

City of Rotterdam (2009) Rotterdam Climate Proof: 2009Adaptation Programme, www.rotterdamclimateinitiative.nl/documents/Documenten/RCP_adaptatie_eng.pdf, last accessed 14 October 2010

City of Rotterdam (undated) Rotterdam Climate Proof:The Rotterdam Challenge on Water and ClimateAdaptation, www.climateinitiative.eu/documents/Documenten/RCP_folder_eng.pdf, last accessed 14 October 2010

City of São Paulo (2009) Instrui a Política de Mudança doClima no Município de São Paulo, Lei no 14933sancionada em 05/06/2009 e publicada no DiárioOficial do Município em 06/06/2009, A. C. M. d. S.Paulo, City of São Paulo, Brazil

Ciudad de Mexico (2008) Programa de Acción Climática,Gobierno del Distrito Federal, Ciudad de Mexico

Clapp, C., A. Leseur, O. Sartor, G. Briner and J. Corfee-Morlot (2010) Cities and Carbon Market Finance:Taking Stock of Cities Experience with CleanDevelopment Mechanism (CDM) and JointImplementation (JI), OECD Environmental WorkingPaper No 29, OECD Publishing, Paris, www.oecd.org/dataoecd/18/43/46501427.pdf, last accessed 10 December 2010

Climate Alliance (undated) ‘Climate Alliance’,www.klimabuendnis.org/, last accessed 28 October2010

Climate Fund Update (undated a) ‘Special ClimateChange Fund’, www.climatefundsupdate.org/listing/special-climate-change-fund, last accessed 6 October2010

Climate Fund Update (undated b) ‘Least DevelopedCountries Fund (LDCF)’, www.climatefundsupdate.org/listing/least-developed-countries-fund, last accessed28 October 2010

Climate Fund Update (undated c) ‘Adaptation Fund’,www.climatefundsupdate.org/listing/adaptation-fund,last accessed 6 October 2010

Climate Investment Funds (undated) ‘The ClimateInvestment Funds’, www.climateinvestmentfunds.org/cif/, last accessed 6 October 2010

Clinton Foundation (undated a) ‘Combating climatechange: Clinton Climate Initiative’, www.clintonfoundation.org/what-we-do/clinton-climate-initiative,last accessed 6 October 2010

Clinton Foundation (undated b) ‘What we do’,www.clintonfoundation.org/what-we-do, last accessed14 October 2010

Cohen, M. and J. Garrett (2010) ‘The food price crisisand urban food (in)security’, Environment andUrbanization 22(2): 467–482

Collier, U. (1997) ‘Local authorities and climate protec-tion in the European union: Putting subsidiarity intopractice?’, Local Environment: The InternationalJournal of Justice and Sustainability 2(1): 39–57

Colombo, A., D. Etkin and B. Karney (1999) ‘Climatevariability and the frequency of extreme temperatureevents for nine sites across Canada: Implications forpower usage’, Journal of Climate 12: 2490–2502

Concejo de Bogotá (2008) Proyecto de Acuerdo No 641de 2008 ‘Por medio cual se dictan normas para elManejo del Arbolado del Distrito Capital y se dictanotras disposiciones’, City of Bogotá, Colombia

Costello, A., M. Abbas, A. Allen, S. Ball, S. Bell, R.Bellamy, S. Friel, N. Groce, A. Johnson, M. Kett, M.Lee, C. Levy, M. Maslin, D. McCoy, B. McGuire, H.

Montgomery, D. Napier, C. Pagel, J. Patel, J. A. deOliveira, N. Redclift, H. Rees, D. Rogger, J. Scott, J.Stephenson, J. Twigg, J. Wolff and C. Patterson (2009)‘Managing the health effects of climate change’,Lancet 373(9676): 1693–1733

Coutts, A. M., J. Beringer and N. J. Tapper (2008)‘Impact of increasing urban density on local climate:Spatial and temporal variations in the surface energybalance in Melbourne, Australia’, Journal of AppliedMeteorology and Climatology 46(4): 477–493

Crass, M. (2008) ‘Reducing CO2 emissions from urbantravel: Local policies and national plans’, OECDInternational Conference, Competitive Cities andClimate Change, 2nd Annual Meeting of the OECDRoundtable Strategy for Urban Development, 9–10October 2008, Milan, Italy

Crespin, J. (2006) ‘Aiding local action: The constraintsfaced by donor agencies in supporting effective, pro-poor initiatives on the ground’, Environment andUrbanization 18(2): 433–450

Cross, J. (2001) ‘Megacities and small towns: Differentperspectives on hazard vulnerability’, EnvironmentalHazard 3(2): 63–80

Dalal-Clayton, B. (2003) ‘The MDGs and sustainabledevelopment: The need for a strategic approach’, inD. Satterthwaite (ed) The Millennium DevelopmentGoals and Local Processes: Hitting the Target orMissing the Point, IIED, London, pp73–91

Dalton, M., B. O’Neill, A. Prskawetz, L. Jiang and J.Pitkin (2008) ‘Population aging and future carbonemissions in the United States’, Energy Economics30(2): 642–675

Darch, G. (2006) ‘The impacts of climate change onLondon’s transport systems’, CIWEM MetropolitanBranch Climate Change Conference, 22 February2006

Darido, G., M. Torres-Montoya and S. Mehndiratta(2009) ‘Urban transport and CO2 emissions: Someevidence from Chinese cities’, World Bank WorkingPaper, www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2010/07/21/000334955_20100721033904/Rendered/PDF/557730WP0P11791June020091EN105jan10.pdf,last accessed 12 October 2010

Davies, A. R. (2005) ‘Local action for climate change:Transnational networks and the Irish experience’,Local Environment 10(1): 21–40

de Bono, A., G. Giuliani, S. Kluser and P. Peduzzi (2004)‘Impacts of summer 2003 heat wave in Europe’, EarlyWarning on Emerging Environmental Threats 2, UnitedNations Environment Programme, Nairobi, Kenya

De Lucia, V. and R. Reibstein (2007) ‘Common but differ-entiated responsibility’, in C. J. Cleveland (ed)Encyclopedia of Earth, Environmental InformationCoalition, National Council for Science and theEnvironment, Washington, DC, www.eoearth.org/article/Common_but_differentiated_responsibility,last accessed 6 October 2010

de Sherbinin, A., A. Schiller and A. Pulsipher (2007)‘The vulnerability of global cities to climate hazards’,Environment and Urbanization 19(1): 39–64

Deangelo, B. J. and L. D. D. Harvey (1998) ‘The jurisdic-tional framework for municipal action to reducegreenhouse gas emissions: Case studies from Canada,the USA and Germany’, Local Environment 3(2):111–136

Delgado, P. M. (2008) ‘Mega cities and climate change:Mexico City Climate Action Program 2008–2012, Apresentation’, www.lead.colmex.mx/docs/MARTHA%20DELGADO_megacities%20and%20climate%20change.ppt, last accessed 12 October 2010

253References

Demetriades, J. and E. Esplen (2008) Gender andClimate Change: Mapping the Linkages – ScopingStudy on Knowledge and Gaps, Institute ofDevelopment Studies, London

Department of Ecology, State of Washington (undated)2008 Comprehensive Plan, www.ecy.wa.gov/climatechange/2008CompPlan.htm, last accessed 6 October 2010

Department of Energy and Climate Change (undated)‘UK Climate Change Programme’, www.decc.gov.uk/en/content/cms/what_we_do/change_energy/tackling_clima/programme/programme.aspx, lastaccessed 6 October 2010

Dhakal, S. (2004) Urban Energy Use and Greenhouse GasEmissions in Asian Mega-Cities: Policies forSustainable Future, Institute for Global EnvironmentalStrategies, Hayama, Japan

Dhakal, S. (2006) ‘Urban transportation and the environ-ment in Kathmandu Valley, Nepal: Integrating globalcarbon concerns into local air pollution management’,Institute for Global Environmental Strategies,Hayama, Japan

Dhakal, S. (2008) ‘Climate change and cities: Themaking of a climate friendly future’, in P. Droege (ed)Urban Energy Transition: From Fossil Fuels toRenewable Power, Elsevier Science, Oxford,pp173–192

Dhakal, S. (2009) ‘Urban energy use and carbon dioxideemissions from cities in China and policyimplications’, Energy Policy 37(11): 4208–4219

Díaz Palacios, J. and L. Miranda (2005) ‘Concertación(reaching agreement) and planning for sustainabledevelopment in Ilo, Peru’, in S. Bass, H. Reid, D.Satterthwaite and P. Steele (eds) Reducing Povertyand Sustaining the Environment, Earthscan, London,pp254–278

Disch, D. (2010) ‘A comparative analysis of the “develop-ment dividend” of Clean Development Mechanismprojects in six host countries’, Climate andDevelopment 2(1): 50–64

Dlamini, D. (2006) ‘Greening Soweto gets R2.2m cashinjection’, Joburgnews, http://joburgnews.co.za/2006/dec/dec7_soweto.stm, last accessed 14October 2010

Dlugolecki, A. (ed) (2001) Climate Change andInsurance, Chartered Insurance Institute, London

Dodman, D. (2009) ‘Blaming cities for climate change?An analysis of urban greenhouse gas emissions inven-tories’, Environment and Urbanization 21(1):185–201

Dodman D. and D. Satterthwaite (2008) ‘Institutionalcapacity, climate change adaptation and the urbanpoor’, IDS Bulletin 39(4): 67–74

Dodman, D. and D. Satterthwaite (2009) ‘The costs ofadapting infrastructure to climate change’, in M.Parry, N. Arnell, P. Berry, D. Dodman, S. Fankhauser,C. Hope, S. Kovats, R. Nicholls, D. Satterthwaite, R.Tiffin and T. Wheeler (eds) Assessing the Costs ofAdaptation to Climate Change: A Review of theUNFCCC and Other Recent Estimates, IIED andGrantham Institute, London, http://pubs.iied.org/pdfs/11501IIED.pdf, last accessed 7 December 2010,pp73–89

Dodman D., J. Ayers and S. Huq (2009) ‘Buildingresilience’, in Worldwatch Institute (ed) State of theWorld 2009: Into a Warming World, Washington, DC

Dodman D., D. Mitlin, and J. C. Rayos Co (2010a)‘Victims to victors, disasters to opportunities:Community-driven responses to climate change in thePhilippines’ International Development PlanningReview 32(1): 1–26

Dodman, D., E. Kibona and L. Kiluma (2010b)‘Tomorrow is too late: Responding to social andclimate vulnerability in Dar es Salaam, Tanzania’,Unpublished case study prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Donnelly, J. and J. Woodruff (2007) ‘Intense hurricaneactivity over the past 5,000 years controlled by ElNiño and the West African monsoon’, Nature447(7143): 465–468

Donner, S., W. Skirving, C. Little, M. Oppenheimer andO. Hoegh-Guldberg (2005) ‘Global assessment ofcoral bleaching and required rates of adaptationunder climate change’, Global Change Biology 11(12):2251–2265

Dossou, K. and B. Glehouenou-Dossou (2007) ‘Thevulnerability to climate change of Cotonou (Benin):The rise in sea level’, Environment and Urbanization19(1): 65–79

Douglas, I., K. Alam, M. Maghenda, Y. McDonnell, L.McLean and J. Campbell (2008) ‘Unjust waters:Climate change, flooding and the urban poor inAfrica’, Environment and Urbanization 20(1):187–206

Dubeux, C. and E. La Rovere (2010) ‘The contribution ofurban areas to climate change: The case study of SãoPaulo, Brazil’, Unpublished case study prepared forthe Global Report on Human Settlements 2011,www.unhabitat.org/grhs/2011

Easterling, W. E., B. H. Hurd and J. B. Smith (2004)‘Coping with global climate change: The role ofadaptation in the United States’, Pew Center onGlobal Climate Change, Arlington, VA

EEA (European Environment Agency) (2005)Vulnerability and Adaptation to Climate Change inEurope, EEA Technical Report No 7/2005, EuropeanEnvironment Agency Copenhagen, Denmark or Officefor Official Publications of the EC, Luxembourg

Elsasser, H. and R. Bürki (2002) ‘Climate change as athreat to tourism in the Alps’, Climate Research20(3): 253–257

Elsner, J., J. Kossin and T. Jagger (2008) ‘The increasingintensity of the strongest tropical cyclones’, Nature455(7209): 92–95

Emanuel, K. (2005) ‘Increasing destructiveness of tropi-cal cyclones over the past 30 years’, Nature436(7051): 686–688

Enarson, E. (2000) Gender and Natural Disasters, ILO, InFocus Programme on Crisis Response andReconstruction, Working Paper 1, pp4–29

Enarson, E. and B. Phillips (2008) ‘Invitation to a newfeminist disaster sociology: Integrating feministtheory and methods’, in B. Phillips and B. H. Morrow(eds) Women and Disasters: From Theory to Practice,International Research Committee on Disaster,Xlibris, pp41–74

Energy Cities (undated) ‘Association’, www.energy-cities.eu/-Association,8-, last accessed 6 October 2010

Energy Information Administration (undated) ‘Officialenergy statistics from the US Government: Countryanalysis briefs’, www.eia.doe.gov/emeu/cabs/index.html, last accessed 12 October 2010

Energy Planning Knowledge Base (undated) CIS TowerManchester, www.pepesecenergyplanning.eu/archives/67, last accessed 14 October 2010

Environment Canada (2001) Threats to Sources ofDrinking Water and Aquatic Ecosystems Health inCanada, National Water Research Institute ScientificAssessment Report Series No 1, National WaterResources Research Institute, Burlington, Ontario


Environmental Management Department (2003)eThekwini Environmental Services Management Plan,Unpublished report, eThekwini MetropolitanMunicipality, South Africa

Enz, R. (2000) ‘The S-Curve relation between per-capitaincome and insurance penetration’, Geneva Papers onRisk and Insurance: Issues and Practice 25(3):396–406

EU (European Union) (undated) ‘Covenant of mayorscommitted to local sustainable energy’, www.eumayors.eu/about_the_covenant/index_en.htm, last accessed 6 October 2010

European Commission (2007) ‘Carbon footprint: What itis and how to measure it’, http://lca.jrc.ec.europa.eu/Carbon_footprint.pdf, last accessed 11 October 2010

European Commission (2009) EU Action against ClimateChange: Leading Global Action to 2020 and Beyond,European Commission, Luxembourg,http://ec.europa.eu/environment/climat/pdf/brochures/post_2012_en.pdf, last accessed 6 October 2010

European Investment Bank (2010) ‘The EIB and climatechange’, www.eib.org/attachments/strategies/clima_en.pdf, last accessed 6 October 2010

Ewing, R., K. Bartholomew, S. Winkelman, J. Walters andD. Chen (2008) Growing Cooler: the Evidence onUrban Development and Climate Change, Urban LandInstitute, Washington, DC

Federation of Canadian Municipalities (2009) MunicipalResources for Adapting to Climate Change, Federationof Canadian Municipalities, Ottawa, Canada

Figueres, C. (2010) ‘Address to the Swiss Re high-leveladaptation event on risk and resiliency, New York, 20 September 2010’, http://unfccc.int/files/press/statements/application/pdf/100920_speech_cf_adaptation_new_york.pdf

Flyvbjerg, B. (2002) ‘Bringing power to planningresearch: One researcher’s praxis story’, Journal ofPlanning Education and Research 21(4): 353–366

Foresight (2008) Powering Our Lives: Sustainable EnergyManagement and the Built Environment, Final projectreport, Government Office for Science, London

Forstall, R. L., R. P. Greene and J. B. Pick (2009) ‘Whichare the largest? Why lists of major urban areas vary sogreatly’, Tijdschrift voor economische en socialegeografie 100(3): 277–297

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R.Betts, D. W. Fahey, J. Haywood, J. Lean, D.C. Lowe,G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulzand R. Van Dorland (2007) ‘Changes in atmosphericconstituents and in radiative forcing’, in S. Solomon,D. Qin, M. Manning, Z. Chen, M. Marquis, K. B.Averyt, M. Tignor and H. L. Miller (eds) ClimateChange 2007: The Physical Science Basis,Contribution of Working Group I to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge and New York

Fothergill, A., E. G. M. Maestas, and J. D. Darlington(1999) ‘Race, ethnicity and disasters in the UnitedStates: A review of the literature’, Disasters 23(2):156–174

Frayssinet, F. (2009) ‘Casas ecológicamente correctas …y blindadas’, Inter-Press Service, http://ipsnoticias.net/nota.asp?idnews=92018, last accessed 14 October2010

Freeman P. K. and K. Warner (2001) Vulnerability of Infra-structure to Climate Variability: How Does this AffectInfrastructure Lending Policies?, Report commissionedby the Disaster Management Facility of the WorldBank and the ProVention Consortium, Washington, DC

Fricas, J. and Martz, T. (2007) ‘The impact of climatechange on water, sanitation, and diarrheal diseases inLatin America and the Caribbean’, PopulationReference Bureau, www.prb.org/Articles/2007/ClimateChangeinLatinAmerica.aspx, last accessed 29 October 2010

Frich, P., L. V. Alexander, P. Della-Marta, B. Gleason, M.Haylock, A. M. G. K. Tank and T. Peterson (2002)‘Observed coherent changes in climatic extremesduring the second half of the twentieth century’,Climate Research 19(3): 193–212

Füssel, H.-M. (2009) ‘Review and quantitative analysisof indices of climate change exposure, adaptivecapacity, sensitivity, and impacts’, Background Notedeveloped for World Development Report 2010:Development and Climate Change, PotsdamInstitute for Climate Impact Research, Potsdam,Germany

Gagnon-Lebrun, F. and S. Agrawala (2006) ‘Progress onadaptation to climate change in developed countries:An analysis of broad trends’, ENV/EPOC/GSP(2006)1/FINAL, OECD, Paris www.oecd.org/dataoecd/49/18/37178873.pdf, last accessed 14 October 2010

Garside, B., J. MacGregor and B. Vorley (2007) ‘Milesbetter? How “fair miles” stack up in the sustainablesupermarket’, IIED Sustainable Development Opinion,December

Gavidia, J. (2006) ‘Priority goals in Central America: Thedevelopment of sustainable mechanisms for participa-tion in local risk management’, in Milenio Ambiental,Journal of the Urban Environment Programme of theInternational Development Research Centre,Montevideo 4: 56–59

GCCA (Global Climate Change Alliance) (undated a)‘Background and objectives’, www.gcca.eu/pages/14_2-Background-and-Objectives.html, last accessed6 October 2010

GCCA (undated b) ‘Beneficiary countries’,www.gcca.eu/pages/41_2-GCCA-Beneficiaries.html,last accessed 6 October 2010

GCCA (undated c) ‘Priority areas’, www.gcca.eu/pages/30_2-Priority-areas.html, last accessed 6 October2010

GEF (Global Environmental Facility) (undated) ‘GEF-administered trust funds’, www.thegef.org/gef/node/2042, last accessed 6 October 2010

Giannakopoulos, C. and B. E. Psiloglou (2006) ‘Trends inenergy load demand for Athens, Greece: Weather andnon-weather related factors’, Climate Research 31:97–108

Gibbs, D. (2000) ‘Ecological modernization, regionaleconomic development and regional developmentagencies’, Geoforum 31(1): 9–19

Gilbertson, T. and O. Reyes (2009) ‘Carbon trading –how it works and why it fails’, in L. Lohmann (ed)Critical Currents, Dag Hammarskjöld FoundationPublishers, Uppsala, www.tni.org/carbon-trade-fails,last accessed 6 October 2010

Girardet, H. (1998) ‘Sustainable cities: A contradictionin terms?’, in E. Fernandes (ed) EnvironmentalStrategies for Sustainable Development in UrbanAreas: Lessons from Africa and Latin America,Ashgate, Aldershot, pp193–209

GLA (Greater London Authority) (2007) Action Today toProtect Tomorrow: The Mayor’s Climate ChangeAction Plan, Greater London Authority, London

GLA (2008) The London Plan: Spatial DevelopmentStrategy for Greater London, (Consolidated with alter-ations since 2004), Greater London Authority,London

255References

GLA (2010) The Draft Climate Change AdaptationStrategy for London – Public Consultation Draft,Greater London Authority, City Hall, London,http://static.london.gov.uk/mayor/priorities/docs/Climate_change_adaptation_080210.pdf, lastaccessed 25 October 2010

Glaeser, E. and M. Kahn (2008) The Greenness of Cities:Carbon Dioxide Emissions and Urban Development,Harvard Kennedy School, Taubman Center for Stateand Local Government – Working Paper

Gomes, J., J. Nascimento and H. Rodrigues H (2008)‘Estimating local greenhouse gas emissions: A casestudy on a Portuguese municipality’, InternationalJournal of Greenhouse Gas Control 2(1): 130–135

Gomez Martin, M. B. (2005) ‘Weather, climate, andtourism: A geographical perspective’, Annals ofTourism Research 32(3): 571–591

Gore, C., P. Robinson and R. Stren (2009) ‘Governanceand climate change: Assessing and learning fromCanadian cities’, Paper prepared for the Fifth UrbanResearch Symposium, Cities and Climate Change:Responding to an Urgent Agenda, 28–30 June,Marseille, France

Gottdiener, M. and L. Budd (2005) Key Concepts inUrban Studies, Sage, London

Gouveia, N., S. Hajat and B. Armstrong (2003)‘Socioeconomic differentials in the temperature–mortality relationship in São Paulo, Brazil’,International Journal of Epidemiology 32(3): 390–397

Graham, S. and S. Marvin (2001) Splintering Urbanism,Routledge, London

Granberg, M. and I. Elander (2007) ‘Local governanceand climate change: Reflections on the Swedishexperience’, Local Environment 12(5): 537–548

Graves, H. M. and M. C. Phillipson (2000) PotentialImplications of Climate Change in the Built Environ-ment, BRE Center for Environmental Engineering/BRE East Kilbride, FBE Report 2 December 2000,Construction Research Communications Ltd, UK

Greene, D. L., J. R. Kahn and R. C. Gibson (1999) ‘Fueleconomy rebound effect of U.S. household vehicles’,Energy Journal 20(3): 1–31

Greene, D. L., P. R. Boudreaux, D. J. Dean, W. Fulkerson,A. L. Gaddis, R. L. Graham, R. L. Graves, J. L. Hopson,P. Hughes, M.V. Lapsa, T. E. Mason, R. F. Standaert, T. J. Wilbanks and A. Zucker (2010) ‘The importanceof advancing technology to America’s energy goals’,Energy Policy 38(8): 3886–3890

Greenpeace (2008) China after the Olympics: Lessonsfrom Beijing, Greenpeace, Beijing

Grimm, N. B, S. H. Faeth, N. E. Golubiewski, C. L.Redman, J. Wu, X. Bai and J. M. Briggs (2008) ‘Globalchange and the ecology of cities’, Science 319(5864):756–760

Gulden, T. (2009) ‘The security challenges of climatechange: Who is at risk and why?’, in M. Ruth and M.Ibarrarán (eds) Distributional Impacts of ClimateChange, Edward Elgar Publishing, Cheltenham, Glos,UK

Gupta, J. and H. van Asselt (2006) ‘Helpingoperationalise article 2: A trans disciplinary method-ological tool for evaluating when climate change isdangerous’, Global Environmental Change 16(1):83–94

Gupta, R. and S. Chandiwala (2009) ‘A critical andcomparative evaluation of approaches and policiesto measure, benchmark, reduce and manage CO2emissions from energy use in the existing buildingstock of developed and rapidly-developing countries– case studies of UK, USA, and India’, Paperprepared for the Fifth Urban Research Symposium,

Cities and Climate Change: Responding to anUrgent Agenda, 28–30 June, Marseille, France,http://siteresources.worldbank.org/INTURBANDEVELOPMENT/Resources/336387-1256566800920/gupta.pdf, last accessed 12 October 2010

Haigh, C. and B. Vallely (2010) Gender and the ClimateChange Agenda: The Impacts of Climate Change onWomen and Public Policy, Women’s EnvironmentalNetwork, London

Haines, A., R. S. Kovats, D. Campbell-Lendrum and C.Corvalan (2006) ‘Climate change and human health:Impacts, vulnerability, and mitigation’, Lancet367(9528): 2101–2109

Hall, J. W., P. B. Sayers and R. J. Dawson (2005)‘National-scale assessment of current and future floodrisk in England and Wales’, Natural Hazards 36(1–2):147–164

Halweil, B. (2002) Home Grown: The Case for LocalFood in a Global Market, Worldwatch Paper 163,www.worldwatch.org/system/files/EWP163.pdf, lastaccessed 12 October 2010

Hamilton, J., D. Maddison and R. Tol (2005) ‘Climatechange and international tourism: A simulationstudy’, Global Environmental Change 15: 253–266

Hammarby Sjöstad (2010) The Hammarby Model,Hammarby Sjöstad, Stockholm, Sweden

Hammer, S. (2009) ‘Capacity to act: The critical determi-nant of local energy planning and programimplementation’, Paper prepared for the Fifth UrbanResearch Symposium, Cities and Climate Change:Responding to an Urgent Agenda, 28–30 June,Marseille, France

Handy, S., C. Xinyu and P. Mokhtarian (2005)‘Correlation or causality between the built environ-ment and travel behaviour? Evidence from northernCalifornia’, Transportation Research Part D 10(6):427–444

Hardoy, J. and G. Pandiella (2009) ‘Urban poverty andvulnerability to climate change in Latin America’,Environment and Urbanization 21(1): 203–224

Hardoy, J. E., D. Mitlin and D. Satterthwaite (1992)Environmental Problems in Third World Cities,Earthscan, London

Hardoy, J. E., D. Mitlin and D. Satterthwaite (2001)Environmental Problems in an Urbanizing World:Finding Solutions for Cities in Africa, Asia and LatinAmerica, Earthscan, London

Harlan, S. L., A. Brazel, L. Prashad, W. Stefanov and L.Larsen (2006) ‘Neighbourhood microclimates andvulnerability to heat stress’, Social Science andMedicine 63(11): 2847–2863

Harrison, G. P. and H. W. Whittington (2002)‘Susceptibility of the Batoka Gorge hydroelectricscheme to climate change’, Journal of Hydrology264(1–4): 230–241

Harvey, D. (1996) Justice, Nature and the Geography ofDifference, Blackwell Publishers, Cambridge, MA

Harvey, L. (1993) ‘Tackling urban CO2 emissions inToronto’, Environment 35(7): 16–44

Hasan, A. (2006) ‘Orangi Pilot Project: The expansion ofwork beyond Orangi and the mapping of informalsettlements and infrastructure’, Environment andUrbanization 18(2): 451–480

Hasan, A. (2010) Participatory Development: TheStory of the Orangi Pilot Project-Research andTraining Institute and the Urban Resource Centre,Karachi, Pakistan, Oxford University Press,Oxford, UK

Heede, R. (2006) Aspen Greenhouse Gas Emissions2004, Climate Mitigation Services, City of Aspen,Aspen, CO


Held, D. and A. F. Hervey (2009) ‘Democracy, climatechange and global governance: Democratic agencyand the policy menu ahead’, Policy Network Paper,Policy Network, London, www.policy-network.net/uploadedFiles/Publications/Publications/Democracy%20climate%20change%20and%20global%20governance.pdf, last accessed 6 October 2010

Hemmati, M. (2008) ‘Gender perspectives on climatechange’, Background paper to the Interactive ExpertPanel, United Nations Commission on the Status ofWomen, 52nd session, 25 February–7 March 2008,New York, NY

Hendrickson, J. (undated) ‘Energy use in the U.S. foodsystem: A summary of existing research and analysis’,Center for Integrated Agricultural Systems, UW-Madison, www.cias.wisc.edu/wp-content/uploads/2008/07/energyuse.pdf, last accessed 12 October2010

Henry, S., B. Schoumaker and C. Beauchemin (2004)‘The impact of rainfall on the first out-migration: Amulti-level event-history analysis in Burkina Faso’,Population and Environment 25(5): 423–460

Hertwich, E. and G. Peters (2009) ‘Carbon footprint ofnations: A global, trade-linked analysis’,Environmental Science and Technology 43(16):6414–6420

Hintz, G. (2009) ‘Maximizing the returns on adaptationinvestments: Flood prevention in Guyana’,Unpublished draft case study prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Hodgkinson, D., T. Burton, H. Anderson and L. Young(undated) ‘The hour when the ship comes in: Aconvention for persons displaced by climate change’,www.ccdpconvention.com/documents/Hour_When_Ship_Comes_In.pdf, last accessed 14 October 2010

Hodson, M. and S. Marvin (2007) ‘Understanding therole of the national exemplar in constructing “strate-gic glurbanization”’, International Journal of Urbanand Regional Research 31(2): 303–325

Hoffmann, M. J. (2011) Climate Governance at theCrossroads: Experimenting with a Global Responseafter Kyoto, Oxford University Press, London

Holden, E. and I. T. Norland (2005) ‘Three challenges forthe compact city as a sustainable urban form:Household consumption of energy and transport ineight residential areas in the greater Oslo region’,Urban Studies 42(12): 2145–2166

Holgate, C. (2007) ‘Factors and actors in climate changemitigation: A tale of two South African cities’, LocalEnvironment 12(5): 471–484

Hughes, T. P. (1989) ‘The evolution of large technologi-cal systems’, in W. E. Bijker, T. P. Hughes and T. Pinch(eds) The Social Construction of TechnologicalSystems, MIT Press, Boston, MA

Hunt, A. and P. Watkiss (2007) ‘Literature review onclimate change impacts on urban city centres: Initialfindings’, Organisation for Economic Co-operationand Development (OECD), Paris

Huq, S., A. Rahman, M. Konate, Y. Sokona and H. Reid(2003) Mainstreaming Adaptation to Climate Changein Least Developed Countries (LDCs), IIED, London

Ibarrarán, M. (2011) ‘Climate’s long-term impacts onMexico’s city urban infrastructure’, Unpublished casestudy prepared for the Global Report on HumanSettlements 2011, www.unhabitat.org/grhs/2011

ICLEI (Local Governments for Sustainability) (2006)ICLEI International Progress Report – Cities forClimate Protection, ICLEI, Oakland

ICLEI (2007) Preparing for Climate Change: A Guidebookfor Local, Regional, and State Governments, Center

for Science in the Earth System, University ofWashington and King County, in association withICLEI, Washington

ICLEI (2008) Draft International Local Government GHGEmissions Analysis Protocol, Release version 1.0,www.iclei.org/fileadmin/user_upload/documents/Global/Progams/GHG/LGGHGEmissionsProtocol.pdf,last accessed 12 October 2010

ICLEI (2010) Cities in a Post-2012 Climate PolicyFramework: Climate Financing for City Development?Views from Local Governments, Experts andBusinesses, ICLEI, Bonn, Germany, www.iclei.org/fileadmin/user_upload/documents/Global/Services/Cities_in_a_Post-2012_Policy_Framework-Climate_Financing_for_City_Development_ICLEI_2010.pdf,last accessed 14 October 2010

ICLEI (undated) ‘Home’, www.iclei.org/index.php?id=iclei-home, last accessed 28 October 2010

ICLEI Australia (2008) Local Government Action onClimate Change: Measures Evaluation Report 2008,Australian Government Department of Environment,Water, Heritage and the Arts and ICLEI, Melbourne,Australia, www.iclei.org/fileadmin/user_upload/documents/ANZ/Publications-Oceania/Reports/0812-CCPMeasuresReport08.pdf, last accessed 15 October 2010

ICLEI, UN-Habitat and UNEP (2009) Sustainable UrbanEnergy Planning: A Handbook for Cities and Towns inDeveloping Countries, UN-Habitat, Nairobi,www.unhabitat.org/pmss/listItemDetails.aspx?publicationID=2839, last accessed 6 October 2010

ICSU, UNESCO and UNU (International Council forScience, United Nations Educational, Scientific andCultural Organization, and United NationsUniversity) (2008) Ecosystem Change and HumanWell-Being Research and Monitoring Priorities Basedon the Findings of the Millennium EcosystemAssessment, International Council for Science, Paris

IEA (International Energy Agency) (2008) World EnergyOutlook 2008, International Energy Agency, Paris

IEA (2009) Cities, Towns and Renewable Energy: Yes inMy Front Yard, International Energy Agency, Paris

IEA (2010) Key World Energy Statistics, OECD/IEA, ParisIFRC (International Federation of Red Cross and Red

Crescent Societies) (2010) World Disasters Report2010: Focus on Urban Risk, IFRC, Geneva

IHDP (International Human Dimensions Programme onGlobal Environmental Change) (undated)‘Urbanization and global environmental change’,www.ihdp.unu.edu/article/read/ugec, last accessed 8December 2010

IIED (International Institute for Environment andDevelopment) (2009) The Adaptation Fund: A Modelfor the Future?, Briefing paper, IIED London,www.iied.org/pubs/pdfs/17068IIED.pdf, last accessed28 October 2010

Inter-American Development Bank (2007) ‘IDB approvesUS$20 million for sustainable energy and climatechange fund’, www.iadb.org/news-releases/2007-08/english/idb-approves-us20-million-for-sustainable-energy-and-climate-change-fund-3987.html, lastaccessed 6 October 2010

IPCC (Intergovernmental Panel on Climate Change)(2001a) ‘Climate change 2001: Synthesis report’, inR. T. Watson, D. L. Albritton, T. Barker, I. A.Bashmakov, O. Canziani, R. Christ, U. Cubasch, O.Davidson, H. Gitay, D. Griggs, K. Halsnaes, J.Houghton, J. House, Z. Kundzewicz, M. Lal, N. Leary,C. Magadza, J. J. McCarthy, J. F. B. Mitchell, J. R.Moreira, M. Munasinghe, I. Noble, R. Pachauri, B.Pittock, M. Prather, R. G. Richels, J. B. Robinson, J.

257References

Sathaye, S. Schneider, R. Scholes, T. Stocker, N.Sundararaman, R. Swart, T. Taniguchi, and D. Zhou(eds) A Contribution of Working Groups I, II, and III tothe Third Assessment Report of the IntergovernmentalPanel on Climate Change, Cambridge UniversityPress, Cambridge

IPCC (2001b) Climate Change 2001: Impacts,Adaptations and Vulnerability, Contribution ofWorking Group II to the Third Assessment Report ofthe Intergovernmental Panel on Climate Change,Cambridge University Press, New York, NY

IPCC (2006) 2006 IPCC Guidelines for NationalGreenhouse Gas Inventories, S. Eggleston, L. Buendia,K. Miwa, T. Ngara and K. Tanabe (eds), Institute forGlobal Environmental Strategies (IGES) Publishers,Kanagawa Japan, www.ipcc-nggip.iges.or.jp/public/2006gl/index.html, last accessed 12 October2010

IPCC (2007a) ‘Climate change 2007: Mitigation ofclimate change’, in B. Metz, O. Davidson, P. Bosch, R.Dave and L. Meyer (eds) Contribution of WorkingGroup III to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork

IPCC (2007b) ‘Climate change 2007: Synthesis report’,in R. K. Pachauri and A. Reisinger (eds) Contributionof Working Groups I, II, and III to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge; www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_synthesis_report.htm, last accessed 13 October 2010

IPCC (2007c) ‘Climate change 2007: The scientificbasis’ in S. Solomon, D. Qin, M. Manning, Z. Chen,M. Marquis, K. B. Averyt, M. Tignor and H. L. Miller(eds) Contributions of Working Group I to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge, www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_wg1_report_the_physical_science_basis.htm, last accessed13 October 2010

IPCC (2007d) ‘Summary for policymakers’, in S.Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis,K. B. Averyt, M. Tignor and H. L. Miller (eds) ClimateChange 2007: The Physical Science Basis,Contribution of Working Group I to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge and New York, pp1–18

IPCC (2007e) ‘Summary for policymakers’, in B. Metz,O. R. Davidson, P. R. Bosch, R. Dave and L. A. Meyer(eds) Climate Change 2007: Mitigation. Contributionof Working Group III to the Fourth Assessment Reportof the Intergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork, pp1–23

IPCC (2007f) ‘Climate change 2007: Impacts, adaptationand vulnerability’, in M. L. Parry, O. F. Canziani, J. P.Palutikof, P. J. van der Linden and C. E. Hanson (eds)Contributions of Working Group II to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge, www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_wg2_report_impacts_adaptation_and_vulnerability.htm,last accessed 13 October 2010

IPCC (undated a) ‘History’, www.ipcc.ch/organization/organization_history.htm, last accessed 6 October2010

IPCC (undated b) ‘Structure’, www.ipcc.ch/organization/organization_structure.htm, lastaccessed 6 October 2010

Iwugo, K. O., B. D’Arcy and R. Andoh (2003) ‘Aspects ofland-based pollution of an African coastal megacity ofLagos’, Paper presented at Diffuse PollutionConference, Dublin: 14/122–124, www.ucd.ie/dipcon/docs/theme14/theme14_32.PDF, last accessed14 October 2010

Jabareen, Y. (2006) ‘Sustainable urban forms: Theirtypologies, models, and concepts’, Journal of PlanningEducation and Research 26(1): 38–52

Jabeen, H., A. Allen and C. Johnson (2010) ‘Built-inresilience: Learning from grassroots coping strategiesto climate variability’, Environment and Urbanization22(2): 415–432

Jacob, K., N. Edelblum and J. Arnold (2000) ‘Riskincrease to infrastructure due to sea level rise, Sectorreport: Infrastructure, the MEC regional assessment’,in C. Rosenzweig and W. D. Solecki (eds) ClimateChange and a Global City: An Assessment of theMetropolitan East Coast (MEC) Region,http://metroeast_climate.ciesin.columbia.edu/reports/infrastructure.pdf, last accessed 9 December 2010

Jessop, B. (2002) The Future of the Capitalist State,Polity, London

Jiang, L. and K. Hardee (2009) ‘How do recent popula-tion trends matter to climate change’, PopulationAction International Working Paper

Johnson, T., C. Alatorre, Z. Romo, F. Liu (2009) Low-Carbon Development for Mexico, World Bank,Washington, DC

Johnsson-Latham, G. (2007) A Study on Gender Equalityas Prerequisite for Sustainable Development: What WeKnow about the Extent to which Women Globally Livein a More Sustainable Way than Men, Leave a SmallerEcological Footprint and Cause Less Climate Change,Report to the Environment Advisory Council,Sweden, www.gendercc.net/fileadmin/inhalte/Dokumente/Actions/ecological_footprint__johnsson-latham.pdf, last accessed 12 October 2010

Jollands, N. (2008) Cities and Energy: A DiscussionPaper, OECD International Conference CompetitiveCities and Climate Change, OECD, Milan

Jones, R. and A. Rahman (2007) ‘Community-basedadaptation’, Tiempo 64: 17–19

Kahn Ribeiro, S., S. Kobayashi, M. Beuthe, J. Gasca, D.Greene, D. S. Lee, Y. Muromachi, P. J. Newton, S.Plotkin, D. Sperling, R. Wit, and P. J. Zhou (2007)‘Transport and its infrastructure’, in B. Metz, O. R.Davidson, P. R. Bosch, R. Dave and L. A. Meyer (eds)Climate Change 2007: Mitigation, Contribution ofWorking Group III to the Fourth Assessment Report ofthe Intergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork, pp323–385

Kalkstein, L. S. and R. E. Davies (1989) ‘Weather andhuman mortality: An evaluation of demographic andinterregional responses in the United States’, Annalsof the Association of American Geographers 79(1):44–64

Karekezi, S., L. Majoro and T. Johnson (2003) ClimateChange and Urban Transport: Priorities for the WorldBank, Working paper, World Bank, Washington, DC

Karol, J. and P. Suarez (2007) ‘Adaptación al cambioclimático, estructuras fractales y trampas discursivas:De la construcción del objeto a la construcción de laacción’, Medio Ambiente y Urbanizacion 67: 25–44

Kates, R., M. Mayfield, R. Torrie and B. Witcher (1998)‘Methods for estimating greenhouse gases from localplaces’, Local Environment 3(3): 279–298


Kehew, R. (2009) ‘Projecting globally, planning locally: Aprogress report from four cities in developingcountries’, in World Meteorological Organization (ed)Climate Sense, Publication for the World ClimateConference-3, Climate Predictions and Informationfor Decision Making, Geneva, Switzerland, 31August–4 September, Tudor Rose, Leicester, UK,pp181–184

Kennedy, C., A. Ramaswami, S. Carney and S. Dhakal(2009a) ‘Greenhouse gas emission baselines forglobal cities and metropolitan regions’, Paperprepared for the Fifth Urban Research Symposium,Cities and Climate Change: Responding to an UrgentAgenda, 28–30 June, Marseille, France

Kennedy, C., J. Steinberger, B. Gasson, Y. Hansen, T.Hillman, M. Havránek, D. Pataki, A. Phdungsilp, A.Ramaswami and G. Villalba Mendez (2009b)‘Greenhouse gas emissions from global cities’,Environmental Science and Technology 43(19):7297–7302

Kern, K. and G. Alber (2008) ‘Governing climate changein cities: Modes of urban climate governance inmulti-level systems’, in Proceedings of the OECDConference on Competitive Cities and ClimateChange, OECD, Paris

Kern, K. and H. Bulkeley (2009) ‘Cities, Europeanizationand multi-level governance: Governing climatechange through transnational municipal networks’,JCMS: Journal of Common Market Studies 47(2):309–332

Kingdon, J. (1984) Agendas, Alternatives and PublicPolicies, Little Brown and Company, Boston andToronto

Kirshen, P., M. Ruth and W. Anderson (2006) ‘Climate’slong-term impacts on urban infrastructures andservices: The case of Metro Boston’, in M. Ruth, K.Donaghy and P. Kirshen (eds) Regional ClimateChange and Variability: Impacts and Responses,Edward Elgar Publishers, Cheltenham, pp190–252

Klein, R., R. J. Nicholls and R. Thomalla (2003)‘Resilience to natural hazards: How useful is thisconcept?’, Global Environmental Change Part B:Environmental Hazards 5(1–2): 35–45

Kolleeny, J. (2006) ‘With geometry and color, OnionFlats concocts a surprise mix of residences behindthe brick shell of a former rag factory’, ArchitecturalRecord, February issue

Kont, A., J. Jaagus and R. Aunap (2003) ‘Climate changescenarios and the effect of sea-level rise for Estonia’,Global and Planetary Change 36(1–2): 1–15

Kousky, C. and S. H. Schneider (2003) ‘Global climatepolicy: Will cities lead the way?’, Climate Policy 3(4):359–372

Kovats, R. S. and R. Akhtar (2008) ‘Climate, climatechange and human health in Asian cities’,Environment and Urbanization 20(1): 165–176

Kumagai, M., K. Ishikawa and J. Chunmeng (2003)‘Dynamics and biogeochemical significance of thephysical environment in Lake Biwa’, Lakes andReservoirs: Research and Management 7(4): 345–348

Kumssa, A. and J. F. Jones (2010) ‘Climate change andhuman security in Africa’, International Journal ofSustainable Development and World Ecology 17:453–461

Kunreuther, H., N. Novemsky and D. Kahneman (2001)‘Making low probabilities useful’, Journal of RiskUncertainty 23(2): 103–120

Kutzbach, M. (2009) ‘Motorization in developingcountries: Causes, consequences, and effectivenessof policy options’, Journal of Urban Economics 65(2):154–166

La Rovere, E. L, C. B. Dubeux, A. Oliveira da Costa, C. A.Pimenteira, F. Frangetto, F. E. Mendes, J. M. G.Monteiro, L. B. Oliveira, N. Baptista and S. K. Ribero(2005) Inventário de Emissões de Gases de EfeitoEstufa do Município de São Paulo [Inventory ofGreenhouse Gases Emissions from São Paulo City],http://ww2.prefeitura.sp.gov.br//arquivos/secretarias/meio_ambiente/Sintesedoinventario.pdf, lastaccessed 12 October 2010

Lagos State Government (2010) Lagos State Urban andRegional Planning and Development Bill 2010 (Law toprovide for the administration of physical planning,urban development, urban regeneration and buildingcontrol in Lagos State and for connected purposes),Gaz. Law 2010 Fashola, 6th Assembly, House ofAssembly, Lagos State, www.lagosstate.gov.ng/uploads/gallery_m2whf09cuhmm71uru4qq.pdf, lastaccessed 15 October 2010

Langer, N. (2004) ‘Natural disasters that reveal cracks inour social foundation’, Educational Gerontology30(4): 275–285

Lasco, R., L. Lebel, A. Sari, A. P. Mitra, N. H. Tri, O. G.Ling and A. Contreras (2007) Integrating CarbonManagement into Development Strategies of Cities –Establishing a Network of Case Studies ofUrbanisation in Asia Pacific, Final Report for the APNProject 2004-07-CMY-Lasco

LCCA (London Climate Change Agency) (2007) MovingLondon towards a Sustainable Low-Carbon City: AnImplementation Strategy, London Climate ChangeAgency, London

Le Treut, H., R. Somerville, U. Cubasch, Y. Ding, C.Mauritzen, A. Mokssit, T. Peterson and M. Prather(2007) ‘Historical overview of climate change’, in S.Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis,K. B. Averyt, M. Tignor and H. L. Miller (eds) ClimateChange 2007: The Physical Science Basis Contributionof Working Group I to the Fourth Assessment Reportof the Intergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork

Leape, J. (2006) ‘The London congestion charge’,Journal of Economic Perspectives 20(4): 157–176

Lebel, L., P. Garden, M. R. N. Banaticla, R. D. Lasco, A.Contreras, A. P. Mitra, C. Sharma, H. T. Nguyen, G. L.Ooi and A. Sari (2007) ‘Integrating carbon manage-ment into the development strategies of urbanizingregions in Asia: Implications of urban function, form,and role’, Journal of Industrial Ecology 11(2): 61–81

Lee, D. H. (1980) ‘Seventy-five years of searching for aheat index’, Environmental Research 22(2): 331–356

Legros, G, I. Havet, N. Bruce and S. Bonjour (2009) TheEnergy Access Situation in Developing Countries: AReview Focusing on the Least Developed Countriesand Sub-Saharan Africa, WHO and UNDP, New York,NY

Lehner, B., G. Czisch and S. Vassolo (2005) ‘The impactof global change on the hydropower potential ofEurope: A model-based analysis’, Energy Policy 33(7):839–855

Lewsey, C., G. Cid and E. Kruse (2004) ‘Assessingclimate change impacts on coastal infrastructure inthe Eastern Caribbean’, Marine Policy 28(5):393–409

Linder, K. P. (1990) ‘National impacts of climate changeon electric utilities’, in J. B. Smith and D. A. Tirpak(eds) The Potential Effects of Global Warming on theUnited States, Environmental Protection Agency,Washington, DC

Lindseth, G. (2004) ‘The Cities for Climate ProtectionCampaign (CCPC) and the framing of local climate

259References

policy’, Local Environment 9(4): 325–336López-Marrero, T. and P. Tschakert (forthcoming) ‘From

theory to practice: Building more resilient communi-ties in flood-prone areas’, Environment andUrbanization 23(1)

Lungo, M. (2007) ‘Gestión de Riesgos nacional y local’,in C. Clarke and C. Pineda (eds) Riesgo y Desastres.Su Gestión Municipal en Centroamérica,Publicaciones especiales sobre el Desarrollo no 3,Inter-American Development Bank, Washington, DC,pp19–27

Mabasi, T. (2009) ‘Assessing the vulnerability, mitigationand adaptation to climate change in Kampala City’,Paper presented at the Fifth Urban ResearchSymposium, Cities and Climate Change: Respondingto an Urgent Agenda, 28–30 June, Marseille, France

Macchi, M. (2008) Indigenous and Traditional Peoplesand Climate Change, IUCN Issues Paper,http://cmsdata.iucn.org/downloads/indigenous_peoples_climate_change.pdf, last accessed 13 October 2010

Mackie, P. (2005) ‘The London congestion charge: A tentative economic appraisal. A comment on thepaper by Prud’homme and Bocajero’, Transport Policy12(3): 288–290

Magrin, G., C. Gay García, D. Cruz Choque, J.C.Giménez, A. R. Moreno, G. J. Nagy, C. Nobre and A. Villamizar (2007) ‘Latin America’, in M. L. Parry,O. F. Canziani, J. P. Palutikof, P. J. van der Linden andC. E. Hanson (eds) Climate Change 2007: Impacts,Adaptation and Vulnerability. Contribution of WorkingGroup II to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change,Cambridge University Press, Cambridge, UK,pp581–615

Manuel-Navarrete, D., M. Pelling and M. Redclift (2008)‘Governance as process: Powerspheres and responsesto climate change in the Mexican Caribbean’,Unpublished paper, King’s College London, London

Markham, V. (2009) U.S. Population, Energy and ClimateChange, Center for Environment and Population,New Canaan, Connecticut, www.cepnet.org/documents/USPopulationEnergyandClimateChangeReportCEP.pdf, last accessed 12 October 2010

Marshall, J., T. McKone, E. Deakin and W. Nazaroff(2005) ‘Inhalation of motor vehicle emissions: Effectsof urban population and land area’, AtmosphericEnvironment 39(2): 283–295

Martine, G. (2009) ‘Population dynamics and policies inthe context of global climate change’, in J. Guzmán,G. Martine, G. McGranahan, D. Schensul and C.Tacoli (eds) Population Dynamics and Climate Change,UNFPA/IIED, pp9–30

Martinot, E., M. Zimmerman, M. van Staden and N.Yamashita (2009) Global Status Report on LocalRenewable Energy Policies, 12 June working draft,Collaborative report by REN21 Renewable EnergyPolicy Network, Institute for Sustainable EnergyPolicies (ISEP) and ICLEI Local Governments forSustainability, http://www.ren21.net/pdf/REN21_LRE2009_Jun12.pdf, last accessed 15 October 2010

Massey, D., W. Axinn and D. Ghimire (2007)Environmental Change and Out-Migration: Evidencefrom Nepal, Population Studies Center ResearchReport 07-615, Institute for Social Research,University of Michigan, Ann Arbor, MI

Maxwell, D., C. Levin, M. Armar-Klemesu, M. Ruel, S.Morris and C. Ahiadeke (1998) Urban Livelihoods andFood and Nutrition Security in Greater Accra, Ghana,IFPRI, Washington, DC

Mayor of London (2007) Action Today to ProtectTomorrow: The Mayor’s Climate Change Action Plan,Greater London Authority, London

McGranahan, G. and D. Satterthwaite (2000)‘Environmental health or ecological sustainability?Reconciling the brown and green agendas in urbandevelopment’, in C. Pugh (ed) Sustainable Cities inDeveloping Countries, Earthscan, London, pp73–90

McGranahan, G., P. Jacobi, J. Songsore, C. Surjadi andM. Kjellen (2001) The Citizens at Risk: From UrbanSanitation to Sustainable Cities, Earthscan, London

McGranahan, G., P. Marcotullio, D. Balk, I. Douglas, T.Elmqvist, W. Rees, D. Satterthwaite, D. Songsore, H.Zlotnick, J. Eades, E. Ezcurra, A. Whyte, X. Bai, H.Imura and H. Shirakawa (2005) ‘Urban systems’, inMillennium Ecosystem Assessment: Ecosystems andHuman Well-Being, Current State and Trends: Findingsof the Condition and Trends Working Group, IslandPress, Washington, DC, pp795–825

McGranahan, G., D. Balk and B. Anderson (2007) ‘Therising tide: Assessing the risks of climate change andhuman settlements in low-elevation coastal zones’,Environment and Urbanization 19(1): 17–37

McGray, D. (2007) ‘Pop-up cities: China builds a brightgreen metropolis’, Wired Magazine, issue 15.05

McGregor, D., D. Simon and D. Thompson (eds) (2006)The Peri-Urban Interface: Approaches to SustainableNatural and Human Resource Use, Earthscan, London

McLeman, R. and B. Smit (2005) ‘Assessing the securityimplications of climate change-related migration’,Paper prepared for International Workshop on HumanSecurity and Climate Change, Oslo, Norway, 21–23June

McMichael, A., R. Woodruff, P. Whetton, K. Hennessy,N. Nicholls, S. Hales, A. Woodward and T. Kjellstrom(2003) Human Health and Climate Change inOceania: A Risk Assessment 2002, CommonwealthDepartment of Health and Ageing, Canberra,Australia

Meehl, G. and C. Tebaldi (2004) ‘More intense, morefrequent, and longer lasting heat waves in the 21stcentury’, Science 305(5686): 994–997

Mendelsohn, R., W. Morrison, M. E. Schlesinger and N. G. Andronova (2000) ‘Country-specific marketimpacts from climate change’, Climatic Change45(3–4): 553–569

Menegat, R. (2002) ‘Participatory democracy andsustainable development: Integrated urban environ-mental management in Porto Alegre, Brazil’,Environment and Urbanization 14(2): 181–206

Merriam-Webster Dictionary (undated) ‘Poleward’,www.merriam-webster.com/dictionary/poleward, lastaccessed 29 October 2010

Meusel, D. and W. Kirch (2005) ‘Lessons to be learnedfrom the 2002 floods in Dresden, German’, in B.Menne, R. Bertollini and W. Kirch (eds) ExtremeWeather Events and Public Health Response, Springer-Verlag, Berlin, pp175–184

Mhapsekar, J. (2010) ‘Parisar Vikas (Presentation)’, StreeMukti Sanghatana, Mumbai

Millennium Ecosystem Assessment (2005) Ecosystemsand Human Well Being, Millennium EcosystemAssessment, World Resources Institute, Island Press,Washington, DC

Mills, E. (2005) ‘Insurance in a climate of change’,Science 309(5737): 1040–1044

Ministério da Ciência e Tecnologia (2004) ComunicaçãoNacional Inicial do Brasil à Convenção do Clima,Ministério da Ciência e Tecnologia, Brazil

Ministry of Foreign Affairs of Denmark (2006) AidManagement Guidelines Glossary, 2nd edition,


http://amg.um.dk/NR/rdonlyres/3845FDB0-028B-4866-AB9B-1DCB7E83A905/0/AMGGlossaryFeburary2006finaldoc.pdf, lastaccessed 14 October 2010

Mitlin, D. (2008) ‘With and beyond the state: Co-production as a route to political influence, powerand transformation for grassroots organizations’,Environment and Urbanization 20(2): 339–360

Mitlin, D. and D. Dodman (forthcoming) ‘Questioningcommunity-based adaptation’, Paper in preparation

Monni, S. and F. Raes (2008) ‘Multilevel climate policy:The case of the European Union, Finland andHelsinki’, Environmental Science & Policy 11(8):743–755

Monstadt, J. (2009) ‘Conceptualizing the politicalecology of urban infrastructures: Insights fromtechnology and urban studies’, Environment andPlanning A 41(8): 1924–1942

Moore, M. (2008) ‘China’s pioneering eco-city ofDongtan stalls’, The Daily Telegraph, 18 October2008

Moravcsik, A. and B. Botos (2007) ‘Tatabanya: Localparticipation and physical regeneration of derelictareas’, Presentation given in Krakow, Poland

Moser, C. (2008) ‘Assets and livelihoods: A frameworkfor asset-based social policy’, in C. Moser and A. A.Dani (eds) Assets, Livelihoods and Social Policy,International Bank for Reconstruction andDevelopment/World Bank, Washington, DC, pp43–81

Moser, C. and D. Satterthwaite (2008) Towards Pro-PoorAdaptation to Climate Change in the Urban Centres ofLow- and Middle-Income Countries, IIED HumanSettlements Discussion Paper Series, Climate Changeand Cities 3, London

Moser, C. and D. Satterthwaite (2010) ‘Toward pro-pooradaptation to climate change in the urban centers oflow- and middle-income countries’, in R. Mearns andA. Norton (eds) Social Dimensions of Climate Change:Equity and Vulnerability in a Warming World, WorldBank, Washington, DC, pp231–258

Moser, S. C. (2010) ‘Now more than ever: The need formore societally relevant research on vulnerability andadaptation to climate change’, Applied Geography30(4): 464–474

Mukheibir, P. and G. Ziervogel (2007) ‘Developing amunicipal adaptation plan (MAP) for climate change:The City of Cape Town’, Environment andUrbanization 19(1): 143–158

Murphy, J. (2000) ‘Ecological modernization’, Geoforum31(1): 1–8

Murray, C. J. and A. D. Lopez (1996) The Global Burdenof Disease: A Comprehensive Assessment of Mortalityand Disability from Diseases, Injuries and Risk Factorsin 1990 and Projected to 2020, Harvard UniversityPress, Boston, MA

Murray, D. (2005) Oil and Food: A Rising SecurityChallenge, Earth Policy Institute, Archived,www.energybulletin.net/node/6052, last accessed 13 October 2010

Myers, N. (1997) ‘Environmental refugees’, Populationand Environment 19(2): 167–182

Myers, N. (2005) ‘Environmental refugees: An emergentsecurity issue’, Paper presented at the 13th EconomicForum, Prague, Czech Republic, 23–27 May 2005

National Drought Mitigation Center (2010) DroughtMonitor: State-of-the-Art Blend of Science andSubjectivity, http://drought.unl.edu/dm/index.html,last accessed 13 October 2010

National Weather Service (undated) Glossary of NationalHurricane Center Terms, www.nhc.noaa.gov/aboutgloss.shtml#e, last accessed 29 October 2010

Nchito, W. S. (2007) ‘Flood risk in unplanned settle-ments in Lusaka’, Environment and Urbanization19(2): 539–551

Neuman, M. (2005) ‘The compact city fallacy’, Journal ofPlanning Education and Research 25(1): 11–26

Neumayer, E. and T. Plümper (2007) ‘The genderednature of natural disasters: The impact of catastrophicevents on the gender gap in life expectancy,1981–2002’, Annals of the American Association ofGeographers 97(3): 551–566

New Scientist (2009) ‘Timeline: Climate change’, NewScientist, www.newscientist.com/article/dn9912-timeline-climate-change.html, last accessed28 October 2010

Newcastle City Council (2008) City Consumption,www.newcastle.nsw.gov.au/environment/climate_cam/climatecam, last accessed 15 October 2010

Newman, P. (2006) ‘The environmental impact of cities’,Environment and Urbanization 18(2): 275–295

Newman, P. and J. Kenworthy (1989) ‘Gasoline consump-tion and cities: A comparison of US cities with aglobal survey’, Journal of the American PlanningAssociation 55(1): 24–37

Newman, P. and J. Kenworthy (1999) Sustainability andCities: Overcoming Automobile Dependence, IslandPress, Washington, DC

Nicholls, R. J. and R. Tol (2007) ‘Impacts and responsesto sea-level rise: A global analysis of the SRES scenar-ios over the twenty-first century’, PhilosophicalTransactions of the Royal Society A 364: 1073–1095

Nicholls, R. J., F. M. J. Hoozemans and M. Marchand(1999) ‘Increasing flood risk and wetland losses dueto global sea-level rise: Regional and global analyses’,Global Environmental Change 9(1001): S69–S87

Nicholls, R. J., S. Hanson, C. Herweijer, N. Patmore, S.Hallegatte, J. Corfee-Morlot, J. Chateau and R. Muir-Wood (2008) Ranking Port Cities with High Exposureand Vulnerability to Climate Extremes: ExposureEstimates, OECD Environment Working Papers, No 1,OECD Publishing, Paris, France

Nickson, A. (2010) ‘Cities and climate change:Adaptation in London, UK’, Unpublished case studyprepared for the Global Report on Human Settlements2011, www.unhabitat.org/grhs/2011

Nodvin, S. C. and K. Vranes (2010), ‘Global warming’, inC. J. Cleveland (ed) Encyclopedia of Earth,Environmental Information Coalition, NationalCouncil for Science and the Environment,Washington, DC, www.eoearth.org/article/global_warming, last accessed 21October 2010

Nordhaus, W. D. (2006) ‘The economics of hurricanes inthe United States’, National Bureau of EconomicResearch (NBER) Working paper, http://papers.nber.org/papers/w12813, last accessed 9 December 2010

Norman, J., H. L. MacLean and C. A. Kennedy (2006)‘Comparing high and low residential density: Life-cycle analysis of energy use and greenhouse gasemissions’, Journal of Urban Planning andDevelopment 132(1): 10–21

NRC (National Research Council) (2009) America’sEnergy Future: Technologies and Transformation, USNational Academies of Science/National ResearchCouncil, National Academies Press, Washington, DC

NRC (2010) Adapting to the Impacts of Climate Change,US National Academies of Science/National ResearchCouncil, National Academies Press, Washington, DC

O’Brien, K., L. Sygna and J. E. Haugen (2004)‘Vulnerable or resilient? A multi-scale assessment ofclimate impacts and vulnerability in Norway’,Climatic Change 64(1–2): 193–225

261References

OCHA and IDMC (United Nations Office for theCoordination of Humanitarian Affairs and the InternalDisplacement Monitoring Centre) (2009)‘Monitoring disaster displacement in the context ofclimate change’, www.internal-displacement.org/8025708F004BE3B1/(httpInfoFiles)/12E8C7224C2A6A9EC125763900315AD4/$file/monitoring-disaster-displacement.pdf, last accessed 9 December 2010

OECD (Organisation for Economic Co-operation andDevelopment) (1995) Urban Energy Handbook: GoodLocal Practice, OECD Publication Services, Paris

OECD (2008) ‘Competitive cities in a changing climate:Introductory issue paper’, OECD InternationalConference, Competitive Cities and Climate Change,2nd Annual Meeting of the OECD RoundtableStrategy for Urban Development, OECD Directoratefor Public Governance and Territorial Development,Milan, Italy

OECD (2009) OECD’s Recent Work on Climate Change,OECD Publications, Paris, France, www.oecd.org/dataoecd/60/40/41810213.pdf, last accessed 6October 2010

OECD (2010) Cities and Climate Change, OECDPublishing, http://dx.doi.org/10.1787/9789264091375-en, last accessed 10 December2010

Office of the Deputy Prime Minister (2003) ‘Sustainablecommunities: Building for the future’, Office of theDeputy Prime Minister, London, www.communities.gov.uk/publications/communities/sustainablecommunitiesbuilding, last accessed 15 October 2010

Office of the Governor, California, US (undated) ‘Gov.Schwarzenegger announces first-of-its-kind climateaction coalition at the governors’ Global ClimateSummit 3’, http://gov.ca.gov/press-release/16497/,last accessed 9 December 2010

Oke, T. R. (1982) ‘The energetic basis of the urban heatisland’, Quarterly Journal of the Royal MeteorologicalSociety 108(455): 1–24

Oresanya, O. (2009) ‘Climate change and waste manage-ment’, Presentation, Lagos Waste ManagementAuthority, Lagos

Osbahr, H. and T. Roberts (2007) Climate Change andDevelopment in Africa: Policy Frameworks andDevelopment Interventions for Effective Adaptation toClimate Change, Report of workshop 12 March,University of Oxford, http://african-environments.ouce.ox.ac.uk/events/2007/070312workshopreport.pdf, last accessed 14 October 2010

Overpeck, J., B. Otto-Bliesner, G. Miller, D. Muhs, R.Alley and J. Kiehl (2006) ‘Paleoclimatic evidence forfuture ice-sheet instability and rapid sea-level rise’,Science 311(5768): 1747–1750

Overstreet, S. and B. Burch (2009) ‘Mental health statusof women and children following Hurricane Katrina’,in B. Willinger (ed) Hurricane Katrina and the Womenof New Orleans, Newcomb College Center forResearch on Women, New Orleans

Owens, S. (1992) ‘Energy, environmental sustainabilityand land-use planning’, in M. Breheny (ed)Sustainable Development and Urban Form, Pion,London, pp79–105

Oxfam (2005) The Tsunami’s Impact on Women, Oxfam,Oxford, UK

PADECO (2009a) Cities and Climate Change: DraftComprehensive Report, Report prepared for the WorldBank, 30 April

PADECO (2009b) Cities and Climate Change: LiteratureReview, Report prepared for the World Bank, 30 April

Parker, L., (2006) Climate Change: The European Union’sEmissions Trading System (EU ETS), CRS Report for

Congress, www.usembassy.it/pdf/other/RL33581.pdf,last accessed 6 October 2010

Parry, M., O. Canziani, J. Palutikof, N. Adger, P.Aggarwal, S. Agrawala, J. Alcamo, A. Allali, O.Anisimov, N. Arnell, M. Boko, T. Carter, G. Casassa,U. Confalonieri, R. Cruz, E. de Alba Alcaraz, W.Easterling, C. Field, A. Fischlin, B. Fitzharris, C.García, H. Harasawa, K. Hennessy, S. Huq, R. Jones,L. Bogataj, D. Karoly, R. Klein, Z. Kundzewicz, M. Lal,R. Lasco, G. Love, X. Lu, G. Magrín, L. Mata, B.Menne, G. Midgley, N. Mimura, M. Mirza, J.Moreno, L. Mortsch, I. Niang-Diop, R. Nicholls, B.Nováky, L. Nurse, A. Nyong, M. Oppenheimer, A.Patwardhan, P. Lankao, C. Rosenzweig, S. Schneider,S. Semenov, J. Smith, J. Stone, J. van Ypersele, D.Vaughan, C. Vogel, T. Wilbanks, P. Wong, S. Wu andG. Yohe (2007a) ‘Technical summary’, in M. Parry, O.Canziani, J. Palutikof, P. van der Linden and C.Hanson (eds) Climate Change 2007: Impacts,Adaptation and Vulnerability; Contribution of WorkingGroup II to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change,Cambridge University Press, New York, NY, pp23–78

Parry, M. L., O. F. Canziani, J. P. Palutikof, P. J. van derLinden and C. E. Hanson (eds) (2007b) ClimateChange 2007: Impacts, Adaptation and Vulnerability.Contribution of Working Group II to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge, www.ipcc.ch/publications_and_data/ar4/wg2/en/contents.html, last accessed 14 October2010

Parry, M., N. Arnell, P. Berry, D. Dodman, S. Fankhauser,C. Hope, S. Kovats, R. Nicholls, D. Satterthwaite, R.Tiffin and T. Wheeler (2009) Assessing the Costs ofAdaptation to Climate Change: A Review of theUNFCCC and Other Recent Estimates, InternationalInstitute for Environment and Development/Grantham Institute for Climate Change, London

Parshall, L., S. Hammer and K. Gurney (2009) ‘Energyconsumption and CO2 emissions in urban counties inthe United States with a case study of the New YorkMetropolitan Area’, Paper prepared for the FifthUrban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Parshall, L., M. Haraguchi, C. Rosenzweig and S. A.Hammer (2010) ‘The contribution of urban areas toclimate change: New York City case study’,Unpublished case study prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Patt, A., A. Dazé and P. Suarez (2009) ‘Gender andclimate change vulnerability: What’s the problem,what’s the solution?’, in M. Ruth and M. E. Ibarrarán(eds) Distributional Impacts of Climate Change andDisasters: Concepts and Cases, Edward ElgarPublishers, Cheltenham, UK

Patz, J. A., D. Campbell-Lendrum, T. Holloway and J. A.Foley (2005) ‘Impact of regional climate change onhuman health’, Nature 438(7066): 310–317

Paul, B. (2009) ‘Why relatively fewer people died? Thecase of Bangladesh’s Cyclone Sidr’, Natural Hazards50(2): 289–304

Pauzner, S. (2009) ‘Tel Aviv to get 1st ecological housingproject’, Ynetnews, 3 September

Pearce, F. (2009) ‘Greenwash: The dream of the first eco-city was built on a fiction’, The Guardian, 23 April

Pelling, M. (1997) ‘What determines vulnerability tofloods: A case study in Georgetown, Guyana’,Environment and Urbanization 9(1): 203–226


Pelling, M. (1998) ‘Participation, social capital andvulnerability to urban flooding in Guyana’, Journal ofInternational Development 10(4): 469–486

Pelling, M. (2005) ‘Enhancing safety and security’,Unpublished issues paper prepared for the GlobalReport on Human Settlements 2007,www.unhabitat.org/grhs/2007

Pelling, M., D. Manuel-Navarrete and M. Redclift(2008) ‘Urban transformation and social learningfor climate proofing on Mexico’s Caribbean coast’,Unpublished paper, King’s College London, London

People’s Republic of China (2007) China’s NationalClimate Change Programme, National Developmentand Reform Commission, People’s Republic of China,www.ccchina.gov.cn/WebSite/CCChina/UpFile/File188.pdf, last accessed 28 October 2010

Perelet, R., S. Pegov and M. Yulkin (2007) ‘Climatechange, Russia country paper’, Background paper forthe UN 2007/2008 Human Development Report,http://hdr.undp.org/en/reports/global/hdr2007-8/papers/Perelet_Renat_Pegov_Yulkin.pdf, lastaccessed 7 December 2010

Peters, G. (2008) ‘From production-based to consumption-based national emission inventories’,Ecological Economics 65(1): 13–23

Petterson, J., L. Stanley, E. Glazier and J. Philipp (2006)‘A preliminary assessment of social and economicimpacts associated with Hurricane Katrina’, AmericanAnthropologist 108(4): 643–670

Pew Center on Global Climate Change (2008)‘Summary: India’s national action plan on climatechange’, www.pewclimate.org/international/country-policies/india-climate-plan-summary/06-2008, last accessed 27 October 2010

Pew Center on Global Climate Change (undated)‘Climate action plans’, www.pewclimate.org/what_s_being_done/in_the_states/action_plan_map.cfm, lastaccessed 28 October 2010

Pieterse, E. (2008) City Futures: Confronting the Crisis ofUrban Development, Zed Books, London and NewYork, and UCT Press, Cape Town

Pradhan, E. K., K. P. West, J. Katz, S. C. LeClerq, S. K.Khatry and S. R. Shrestha (2007) ‘Risk of flood-related mortality in Nepal’, Disasters 31(1): 57–70

Prasad, N., F. Ranghieri, F. Shah, Z. Trohanis, E. Kesslerand R. Sinha (2009) Climate Resilient Cities: A Primeron Reducing Vulnerabilities to Disaster, World Bank,Washington, DC

Preston, B. L. and R. N. Jones (2006) Climate ChangeImpacts on Australia and the Benefits of Early Actionto Reduce Global Greenhouse Emissions, Consultancyreport for the Australian Business Roundtable onClimate Change, CSIRO Marine and AtmosphericResearch, Melbourne

PricewaterhouseCoopers (2010) Carbon DisclosureProject 2010: Global 500 Report, www.cdproject.net/CDPResults/CDP-2010-G500.pdf, last accessed 6December 2010

Prowse, M. and L. Scott (2008) ‘Assets and adaptation:An emerging debate’ IDS Bulletin 39(4): 42–52

Prud’homme, R. and J. P. Bocarejo (2005) ‘The Londoncongestion charge: A tentative economic appraisal’,Transport Policy 12(3): 279–287

Puppim de Oliveira, J. A. (2009) ‘The implementation ofclimate change related policies at the subnationallevel: An analysis of three countries’, HabitatInternational 33(3): 253–259

Qi, Y., L. Ma, H. Zhang and H. Li (2008) ‘Translating aglobal issue into local priority: China’s local govern-ment response to climate change’, Journal ofEnvironment Development 17(4): 379–400

Rabe, B. (2007) ‘Beyond Kyoto: Climate change policy inmultilevel governance systems’, Governance 20(3):423–444

Rabinovitch, J. (1992) ‘Curitiba: Towards sustainableurban development’, Environment and Urbanization4(2): 62–73

Rain, D. R., R. Engstrom, C. Ludlow and S. Antos (2011)‘Accra: A vulnerable coastal West African city’,Unpublished case study prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Raleigh, C., L. Jordan and I. Salehyan (2008) ‘Assessingthe impact of climate change on migration andconflict’, Paper commissioned by the World BankGroup for the Social Dimensions of Climate Changeworkshop, Washington, DC, 5–6 March 2008

Rashid, S. (2000) ‘The urban poor in Dhaka City: Theirstruggles and coping strategies during the floods of1998’, Disasters 24(3): 240–253

Räty, R. and A. Carlsson-Kanyama (2010) ‘Energyconsumption by gender in some European countries’,Energy Policy 38(1): 646–649

Raupach, M., G. Marland, P. Ciais, C. Le Quéré, J.Canadell, G. Klepper and C. Fields (2007) ‘Global andregional drivers of accelerating CO2 emissions’, PNAS104(24): 10288–10293

Rees, W. (1992) ‘Ecological footprints and appropriatedcarrying capacity: What urban economics leaves out’,Environment and Urbanization 4(2): 121–130

Rees, W. and M. Wackernagel (1998) Our EcologicalFootprint: Reducing Human Impact on the Earth, NewSociety Publishers, Gabriola Island, British Columbia,Canada

Regional Greenhouse Gas Initiative (undated) ‘Home’,www.rggi.org/home, last accessed 6 October 2010

REN21 (Renewable Energy Policy Network for the 21stCentury) (2009) Renewables Global Status Report:2009 Update, REN21 Secretariat, Paris

Reuveny, R. (2007) ‘Climate change-induced migrationand violent conflict’, Political Geography 26(6):656–673

Revi, A. (2008) ‘Climate change risk: A mitigation andadaptation agenda for Indian cities’, Environment andUrbanization 20(1): 207–230

Reyos, J. (2009) Community-Driven DisasterIntervention: Experiences of the Homeless People’sFederation in the Philippines, HPFP, PACSII and IIED,Manila and London

Rhodes, T. E. (1999) ‘Integrating urban and agriculturewater management in southern Morocco’, Arid LandsNewsletter 45 (spring/summer), http://ag.Arizona.edu/OALS/ALN/aln45/rhodes.html, last accessed 13 October 2010

Richman, E. (2003) ‘Emission trading and the develop-ment critique: Exposing the threat to developingcountries’, Journal of International Law and Politics36: 133–176

Roberts, B., M. Lindfield and X. Bai (2009) ‘Bridging thegap between the supply-side and demand-side CDMprojects in Asian Cities’, Paper prepared for the FifthUrban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Roberts, D. (2008) ‘Thinking globally, acting locally:Institutionalizing climate change at the local govern-ment level in Durban, South Africa’, Environment andUrbanization 20(2): 521–537

Roberts, D. (2010a) ‘Prioritising climate change adapta-tion and local level resiliency in Durban, SouthAfrica’, Environment and Urbanization 22(2):397–414

263References

Roberts, D. (2010b) ‘Thinking globally, acting locally:Institutionalizing climate change within Durban’slocal government’, Briefing paper for the CitiesAlliance, Cities Alliance, Washington, DC

Roberts, D. and N. Diederichs (2002a) ‘Durban’s LocalAgenda 21 programme: Tackling sustainable develop-ment in a post-apartheid city’, Environment andUrbanization 14(1): 189–202

Roberts, D. and N. Diederichs (2002b) Durban’s LocalAgenda 21 Programme 1994–2001: TacklingSustainable Development, Natal Printers, Pinetown

Roberts, J. and P. Grimes (1997) ‘Carbon intensity andeconomic development 1962–1991: A briefexploration of the Environmental Kuznets Curve’,World Development 25(2): 191–198

Robinson, P. J. (2001) ‘On the definition of a heat wave’,Journal of Applied Meteorology 40: 762–775

Rockefeller Foundation (2010) ‘Asian Cities ClimateChange Resilience Network (ACCCRN)’, www.rockefellerfoundation.org/what-we-do/current-work/developing-climate-change-resilience/asian-cities-climate-change-resilience/, last accessed28 October 2010

Rogner, H.-H., D. Zhou, R. Bradley, O. Crabbé, O.Edenhofer, B. Hare, L. Kuijpers and M. Yamaguchi(2007) ‘Introduction’, in B. Metz, O. R. Davidson, P. R. Bosch, R. Dave and L. A. Meyer (eds) ClimateChange 2007: Mitigation, Contribution of WorkingGroup III to the Fourth Assessment Report of theIntergovernmental Panel on Climate, CambridgeUniversity Press, Cambridge and New York, pp95–116

Romero Lankao, P. (2007a) ‘Are we missing the point?Particularities of urbanization, sustainability andcarbon emissions in Latin American cities’,Environment and Urbanization 19(1): 159–175

Romero Lankao, P. (2007b) ‘How do local governments inMexico City manage global warming?’, LocalEnvironment: The International Journal of Justice andSustainability 12(5): 519–535

Romero Lankao, P. (2008) ‘Urban areas and climatechange: Review of current issues and trends’,Unpublished issues paper prepared for the GlobalReport on Human Settlements 2011,www.unhabitat.org/grhs/2011

Romero Lankao, P. (2009) ‘Issues paper’, Unpublishedbackground material prepared for the Global Reporton Human Settlements 2011, www.unhabitat.org/grhs/2011

Romero Lankao, P. (2010) ‘Water in Mexico City: Whatwill climate change bring to its history of water-related hazards and vulnerabilities?’, Environment andUrbanization 22(1): 157–178

Romero Lankao, P. and J. Tribbia (2009) ‘Assessingpatterns of vulnerability, adaptive capacity andresilience across urban centers’, Paper presented atthe Fifth Urban Research Symposium, 28–30 June,Marseille, France

Romero Lankao, P., H. López Villafranco, A. Rosas Huerta,G. Gunther and Z. Correa Armenta (eds) (2005) CanCities Reduce Global Warming? Urban Developmentand Carbon Cycle in Latin America, IAI, UAM-Xochimilco, IHDP, GCP, México, www.globalcarbonproject.org/global/pdf/Romero2005_IAIUurbanCarbonReport.pdf, last accessed 11 October 2010

Romero Lankao, P., D. Nychka and J. Tribbia (2008)‘Development and greenhouse gas emissions deviatefrom “modernization” and “convergence”’, ClimateResearch 38(1): 17–29

Romero Lankao, P., J. L.Tribbia and D. Nychka (2009a)‘Testing theories to explore the drivers of cities’atmospheric emissions’, Ambio 38: 236–244

Romero Lankao, P., O. Wilhelmi, M. Cordova Borbor, D.Parra, E. Behrenz and L. Dawidowski (2009b) ‘Healthimpacts of weather and air pollution – what currentchallenges hold for the future in Latin Americancities’, in K. O’Brien, L. Sygna and J. Wolf (eds) TheChanging Environment for Human Security: NewAgendas for Research, Policy, and Action, GECHS,Oslo, Norway

Rosenzweig, C. and W. D. Solecki (2001) ClimateChange and a Global City: The PotentialConsequences of Climate Variability and Change –Metro East Coast, Report for the US Global ChangeResearch Program, National Assessment of thePotential Consequences of Climate Variability andChange for the United States, Columbia EarthInstitute, New York, NY

Rosenzweig, C., W. Solecki, S.A. Hammer and S.Mehrotra (2010) ‘Cities lead the way in climate-change action’, Nature 467: 909–911

Rosenzweig, C., W. Solecki, S. A. Hammer and S.Mehrotra (2011) Climate Change and Cities: FirstAssessment Report of the Urban Climate ChangeResearch Network, Cambridge University Press,Cambridge, UK

Roy, M. (2009) ‘Planning for sustainable urbanisation infast growing cities: Mitigation and adaptation issuesaddressed in Dhaka, Bangladesh’, HabitatInternational 33(3): 276–286

Ru, G., C. Xiaojing, Y. Xinyu, L. Lankuan, J. Dahe, and L.Fengting (2009) ‘The strategy of energy-relatedcarbon emission reduction in Shanghai’, Energy Policy38(1): 633–638

Ruth, M. and R. Gasper (2008) ‘Water in the urbanenvironment: Meeting the challenges of a changingclimate’, OECD International Conference:Competitive Cities in Climate Change, Milan, Italy

Ruth, M. and M. Ibarrarán (2009) ‘Introduction:Distributional effects of climate change – Social andeconomic implications’, in M. Ruth and M. Ibarrarán(eds) Distributional Impacts of Climate Change,Edward Elgar Publishers, Cheltenham, Glos, UK

Ruth, M. and F. Rong (2006) ‘Research themes andchallenges’, in M. Ruth (ed) Smart Growth andClimate Change, Edward Elgar Publishers,Cheltenham, UK

Ruth, M., B. Davidsdottir and A. Amato (2004) ‘Climatechange policies and capital vintage effects: The casesof US pulp and paper, iron and steel, and ethylene’,Journal of Environmental Management 70(3):235–252

Ruth, M., A. Amato and P. Kirshen (2006) ‘Impacts ofchanging temperatures on heat-related mortality inurban areas: The issues and a case study fromMetropolitan Boston’, in M. Ruth (ed) Smart Growthand Climate Change, Edward Elgar Publishers,Cheltenham, UK, pp364–392

Rutland, T. and A. Aylett (2008) ‘The work of policy:Actor networks, governmentality, and local action onclimate change in Portland, Oregon’, Environmentand Planning D: Society and Space 26(4): 627–646

Sabates-Wheeler, R., T. Mitchell and F. Ellis (2008)‘Avoiding repetition: Time for CBA to engage with thelivelihoods literature?’, IDS Bulletin 39(4): 53–59

Sabine, C. L., M. Heiman, P. Artaxo, D. Bakker, C.-T. A.Chen, C. B. Field, N. Gruber, C. Le Quéré, R. G.Prinn, J. E. Richey, P. Romero Lankao, J. Sathaye, andR. Valentini (2004) ‘Current status and past trends ofthe global carbon cycle’, in C. B. Field and M. R.Raupach (eds) Toward CO2 Stabilization: Issues,Strategies and Consequences, Island Press,Washington, DC


Sailor, D. J (2001) ‘Relating residential and commercialsector electricity loads to climate – evaluating statelevel sensitivities and vulnerabilities’, Energy 26(7):645–657

Sanchez-Rodriguez, R., M. Fragkias and W. Solecki(2008) Urban Responses to Climate Change: A Focuson the Americas – A Workshop Report, InternationalWorkshop Urban Responses to Climate Change, NewYork, NY

Sanders, C. H. and M. C. Phillipson (2003) ‘UK adapta-tion strategy and technical measures: The impacts ofclimate change on buildings’, Building Research andInformation 31(3–4): 210–221

Sandoval, M. J. (2009) ‘Mexico’s national climate changestrategies and international financing mechanisms’,Presentation for the International Financing forClimate Action, 9 July 2009, Brussels,http://europa.eu/epc/pdf/mexico_en.pdf, lastaccessed 27 October 2010

Sanford Housing Co-operative (undated) Carbon 60Project, www.sanford.coop/C60.shtml, last accessed15 October 2010

Sari, A. (2007) ‘Carbon and the city: Carbon pathwaysand decarbonization opportunities in Greater Jakarta,Indonesia’, in R. Lasco, L. Lebel, A. Sari, A. P. Mitra,N. H. Tri, O. G. Ling and A. Contreras (eds)Integrating Carbon Management into DevelopmentStrategies of Cities – Establishing a Network of CaseStudies of Urbanisation in Asia Pacific, Final Report forthe APN project 2004-07-CMY-Lasco, pp125–151

Sassen, S. (1991) The Global City: New York, London,Tokyo, Princeton University Press, Princeton, NJ

Satterthwaite, D. (1997a) ‘Environmentaltransformations in cities as they get larger, wealthier,and better managed’, The Geographic Journal 163(2):216–224

Satterthwaite, D. (1997b) ‘Sustainable cities or citiesthat contribute to sustainable development?’, UrbanStudies 34(10): 1667–1691

Satterthwaite, D. (1999) ‘The key issues and the worksincluded’, in D. Satterthwaite (ed) The EarthscanReader in Sustainable Cities, Earthscan, London,pp3–21

Satterthwaite, D. (2007) The Transition to aPredominantly Urban World and Its Underpinnings,Human Settlements Discussion Paper, IIED, London

Satterthwaite, D. (2008a) ‘“Cities” contribution to globalwarming: Notes on the allocation of greenhouse gasemissions’, Environment and Urbanization 20(2):539–549

Satterthwaite, D. (2008b) ‘Climate change and urbaniza-tion: Effects and implications for urban governance’,United Nations Expert Group Meeting on PopulationDistribution, Urbanization, Internal Migration andDevelopment, UN/POP/EGM-URB/2008/16, NewYork, 21–23 January

Satterthwaite, D. (2009) ‘The implications of populationgrowth and urbanization for climate change’,Environment and Urbanization 21(2): 545–567

Satterthwaite, D. and A. Sverdlik (2009) ‘On energyaccess and use among the urban poor in low- andmiddle-income nations’, Background paper for theGlobal Energy Assessment Report, IIASA

Satterthwaite, D., S. Huq, H. Reid, M. Pelling and P.Romero Lankao (2007a) Adapting to Climate Changein Urban Areas: The Possibilities and Constraints inLow- and Middle-Income Nations, IIED HumanSettlements Discussion Paper Series, Climate Changeand Cities 1, London

Satterthwaite, D., S. Huq, M. Pelling, A. Reid and P.Romero Lankao (2007b) Building Climate Change

Resilience in Urban Areas and among UrbanPopulations in Low- and Middle-income Countries,Research Report Commissioned by the RockefellerFoundation, International Institute for Environmentand Development (IIED), London

Satterthwaite, D., D. Dodman and J. Bicknell (2009a)‘Conclusions: Local development and adaptation’, inJ. Bicknell, D. Dodman and D. Satterthwaite (eds)Adapting Cities to Climate Change: Understandingand Addressing the Development Challenges,Earthscan, London, pp359–383

Satterthwaite, D., S. Bartlett, D. Dodman, D. Hardoy andC. Tacoli (2009b) ‘Social aspects of climate change inurban areas in low- and middle-income areas’, Paperprepared for the Fifth Urban Research Symposium,Cities and Climate Change: Responding to an UrgentAgenda, 28–30 June, Marseille, France

Satterthwaite, D., S. Huq, H. Reid, M. Pelling and P.Romero Lankao (2009c) ‘Adapting to climate changein urban areas: The possibilities and constraints inlow- and middle-income nations’, in J. Bicknell, D.Dodman and D. Satterthwaite (eds) Adapting Cities toClimate Change, Earthscan, London, pp3–34

Scambos, T. A., J. A. Bohlander, C. A. Shuman and P.Skvarca (2004) ‘Glacier acceleration and thinningafter ice shelf collapse in the Larsen B embayment,Antarctica’, Geophysical Research Letters 31(18),doi:10.1029/2004GL020670

Schifferes, S. (2007) ‘China’s eco-city faces growthchallenge’, BBC News, http://news.bbc.co.uk/1/hi/business/6756289.stm, last accessed 15 October2010

Schneider, S. H., S. Semenov, A. Patwardhan, I. Burton,C. H. Magadza, M. Oppenheimer, A. B. Pittock, A.Rahman, J. B. Smith, A. Suarez and F. Yamin (2007)‘Assessing key vulnerabilities and the risk fromclimate change’, in M. L. Parry, O. F. Canziani, J. P.Palutikof, P. J. van der Linden and C. E. Hanson (eds)Climate Change 2007: Impacts, Adaptation andVulnerability, Contribution of Working Group II to theFourth Assessment Report of the IntergovernmentalPanel on Climate Change, Cambridge UniversityPress, Cambridge, UK, pp779–810

Schreurs, M. A. (2008) ‘From the bottom up: Local andsubnational climate change politics’, Journal ofEnvironment Development 17(4): 343–355

Schroeder, H. (2010) ‘Climate change mitigation in LosAngeles, US’, Unpublished case study prepared forthe Global Report on Human Settlements 2011,www.unhabitat.org/grhs/2011

Schroeder, R. A. (1987) ‘Gender vulnerability todrought: A case study of the Hausa socialenvironment’, Natural Hazard Research WorkingPaper 58, Institute of Behavioural Science, Universityof Colorado, pp35–41

Schwaiger, B. and A. Kopets (2009) ‘First steps towardsenergy-efficient cities in Ukraine’, Paper prepared forthe Fifth Urban Research Symposium, Cities andClimate Change: Responding to an Urgent Agenda,28–30 June, Marseille, France

Schwartz, N. and R. Seppelt (2009) ‘Analyzing thevulnerability of European cities resulting from urbanheat island’, World Bank Fifth Urban ResearchSymposium, Marseille, France, 28–30 June

Scott, D., J. Dawson and B. Jones (2007) ‘Climatechange vulnerability of the US northeast winter recreation-tourism sector’, Mitigation and AdaptationStrategies for Global Change 13(5–6): 577–596

Scott, M. J., L. E. Wrench and D. L. Hadley (1994)‘Effects of climate change on commercial buildingenergy demand’, Energy Sources 16(3): 317–332

265References

Secretaría del Medio Ambiente del Distrito Federal(2008) Mexico City Climate Action Plan Program2008–2012: Summary,www.mexicocityexperience.com/documents/climate_change.pdf, last accessed 27 October 2010

Setzer, J. (2009) ‘Subnational and transnational climatechange governance: Evidence from the state and cityof São Paulo, Brazil’, Paper prepared for the FifthUrban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Sgobbi, A. and C. Carraro (2008) Climate ChangeImpacts and Adaptation Strategies in Italy; AnEconomic Assessment, Fondazione Eni Enrico MatteiWorking Paper 170, Berkeley Electronic Press,www.bepress.com/feem/paper170, last accessed 13October 2010

Short, J., K. V. Dender and P. Crist (2008) ‘Transportpolicy and climate change’, in D. Sperling and J. S.Cannon (eds) Reducing Climate Impacts in theTransportation Sector, Springer-Verlag, New York, NY,pp35–48

Shukla, P. R. and S. K. Sharma (undated) Climate ChangeImpacts on Industry in India, Keysheet 8, Departmentof Energy and Climate Change, www.decc.gov.uk/assets/decc/what%20we%20do/global%20climate%20change%20and%20energy/tackling%20climate%20change/intl_strategy/dev_countries/india/india-climate-8-industry.pdf, last accessed 13 October2010

Shukla, P. R., M. Kapshe and A. Garg (2005)Development and Climate: Impacts and Adaptation forInfrastructure Assets in India, OECD, Paris

Silove, D. and Z. Steel (2006) ‘Understanding commu-nity psychosocial needs after disasters: Implicationsfor mental health services’, Journal of PostgraduateMedicine 52(2): 121–125

Silver, J. (2010) Urban Transitions and Climate ChangePilot Study – From the Spiritual Home of Smoke to aCertain (Green) Future: Manchester, Climate Changeand Mitigation Pathways, Unpublished working paper,Department of Geography, Durham University,Durham, UK

Sims, R. E. H., R. N. Schock, A. Adegbululgbe, J.Fenhann, I. Konstantinaviciute, W. Moomaw, H. B.Nimir, B. Schlamadinger, J. Torres-Martínez, C.Turner, Y. Uchiyama, S. J. V. Vuori, N. Wamukonya andX. Zhang (2007) ‘Energy supply’, in B. Metz, O. R.Davidson, P. R. Bosch, R. Dave, L. A. Meyer (eds)Climate Change 2007: Mitigation, Contribution ofWorking Group III to the Fourth Assessment Report ofthe Intergovernmental Panel on Climate Change,Cambridge University Press, Cambridge and NewYork, pp251–322

Singapore Urban Development Authority (2009)‘Singapore: City in a garden’, Unpublished reportpresented to UN-Habitat for the Global Report onHuman Settlements 2011

Sippel, M. and A. Michaelowa (2009) ‘Does globalclimate policy promote low-carbon cities? Lessonslearnt from the CDM’, CIS Working Paper No 49,Centre for Comparative and International Studies,ETH Zurich and University of Zurich, Zurich

Skutsch, M. (2002) ‘Protocols, treaties and action: The “climate change process” viewed through gender spectacles’, Gender & Development 10(2):30–39

Smyth, C. and S. Royle (2000) ‘Urban landslide hazards:Incidence and causative factors in Niterói, Rio deJaneiro State, Brazil’, Applied Geography 20(2):95–117

Sohn, J., S. Nakhooda and K. Baumert (2005)‘Mainstreaming climate concerns at the multilateraldevelopment banks’, WRI Issue Brief, World ResourcesInstitute, Washington, DC, http://pdf.wri.org/mainstreaming_climate_change.pdf, last accessed 6 October 2010

Solar America Cities (2009) Boston Receives RecoveryAct Funding for Solar America Cities Special Project,www.solaramericacities.energy.gov/Cities.aspx?City=Boston, last accessed 15 October 2010

Some, W., W. Hafidz and G. Sauter (2009) ‘Renovationnot relocation: The work of Paguyuban WargaStrenkali (PWS) in Indonesia’, Environment andUrbanization 21(2): 463–476

Sørensen, E. and J. Torfing (2007) Theories ofDemocratic Network Governance, MacMillan,London

Sørensen, E. and J. Torfing (2009) ‘Making governancenetworks effective and democratic through meta-governance’, Public Administration 87(2): 234–258

Sotello, S. (2007) ‘Las eco-casas, una solución habitacio-nal en las zonas más marginales de Buenos Aires’, ElMundo, 25 July 2007

State of São Paulo (2008) São Paulo State, www.theclimategroup.org/programs/policy/states-and-regions/sao-paulo-state/, last accessed 15 October 2010

Stephens, C., R. Patnaik and S. Lewin (1996) ‘This is mybeautiful home: Risk perceptions towards floodingand environment in low income urban communities –A case study in Indore, India’, London School ofHygiene and Tropical Medicine, London

Stern, N. (2006) Stern Review on the Economics ofClimate Change, Cambridge University Press,Cambridge, UK

Stern, N. (2009) Blueprint for a Safer Planet: How toManage Climate Change and Create a New Era ofProgress and Prosperity, The Bodley Head, Oxford,UK

Stern Review Team (2006) What Is the Economics ofClimate Change?, HM Treasury, London

Sterr, H. (2008) ‘Assessment of vulnerability and adapta-tion to sea-level rise for the coastal zone of Germany’,Journal of Coastal Research 24(2): 380–393

Suarez, P., G. Saunders, S. Mendler, I. Lemaire, J. Karoland L. Curtis (2008) ‘Climate related disasters:Humanitarian challenges and design opportunities’,Places 20(2): 62–67

Sugiyama, N. and T. Takeuchi (2008) ‘Local policies forclimate change in Japan’, Journal of EnvironmentDevelopment 17(4): 424–441

The Sunday Times (2009) ‘Yemen could become firstnation to run out of water’, The Sunday Times,www.timesonline.co.uk/tol/news/environment/article6883051.ece

Sustainable Energy Africa (2006) State of Energy inSouth African Cities 2006: Setting a Baseline,Sustainable Energy Africa, Westlake

Suzuki, H., A. Dastur, S. Moffat and N. Yabuki (2009)ECO2 Cities: Ecological Cities as Economic Cities,World Bank, Washington, DC

Sykes, J. (2009) ‘Energy efficiency in the low incomehomes of South Africa’, Climate Strategies Ltd,Cambridge, UK, www.eprg.group.cam.ac.uk/wp-content/uploads/2009/09/isda_south-africa-low-income-housing-study_september-2009-report.pdf,last accessed 13 October 2010

Syukrizal, A., W. Hafidz and G. Sauter (2009)Reconstructing Life: After the Tsunami – The Work ofUplink Banda Aceh in Indonesia, Gatekeeper Series137i, IIED, London


Syvitski, J. P. M., A. J. Kettner, I. Overeem, E. W. H.Hutton, M. T. Hannon, G. R. Brakenridge, J. Day, C.Vorosmarty, Y. Saito, L. Giosan, and R. J. Nicholls(2009) ‘Sinking deltas due to human activities’,Nature Geoscience 2(10): 681–686

Tacoli, C. (2009) ‘Crisis or adaptation? Migration andclimate change in a context of high mobility’,Environment and Urbanization 21(2): 513–525

Takeuchi, A., M. Cropper and A. Bento (2007) ‘Theimpact of policies to control motor vehicle emissionsin Mumbai, India’, Journal of Regional Science 47(1):27–46

Tanner, T., T. Mitchell, E. Polack and B. Buenther (2009)Urban Governance for Adaptation: Addressing ClimateChange Resilience in Ten Asian Cities, IDS WorkingPaper 315, Institute of Development Studies,University of Sussex, UK

Tanser, F. C., B. Sharp and D. le Sueur (2003) ‘Potentialeffect of climate change on malaria transmission inAfrica’, Lancet 362(9398): 1792–1798

Terry, G. (2009) ‘No climate justice without genderjustice: An overview of the issues’, Gender andDevelopment 17(1): 5–18

Thomas, R., E. Rignot, G. Casassa, P. Kanagaratnam, C.Acuña, T. Akins, H. Brecher, E. Frederick, P. Gogineni,W. Krabill, S. Manizade, H. Ramamoorthy, A. Rivera,R. Russell, J. Sonntag, R. Swift, J. Yungel and J. Zwally(2004) ‘Accelerated sea-level rise from WestAntarctica’, Science 306(5694): 255–258

Tolossa, D. (2010) ‘Some realities of urban poor andtheir food security situations: A case study at BertaGibi and Gemachi Safar in the city of Addis Ababa,Ethiopia’, Environment and Urbanization 22(1):179–198

Torres, H. H., H. Alves and M. Aparecida de Oliveira(2007) ‘São Paulo peri-urban dynamics: Some socialcauses and environmental consequences’,Environment and Urbanization 19(1): 207–233

Toulemon, L. and M. Barbieri (2008) ‘The mortalityimpact of the August 2003 heat wave in France:Investigating the “harvesting” effect and other long-term consequences’, Population Studies 62(1): 39–53

Transportation Research Board (2008) Potential Impactsof Climate Change on US Transportation, NationalResearch Council of National Academies, Washington,DC

Turner II, B. L., R. E. Kasperson, P. A. Matson, J. J.McCarthy, R. W. Corell, L. Christensen, N. Eckley, J. X. Kasperson, A. Luers, M. L. Martello, C. Polsky,A. Pulsipher and A. Schiller (2003) ‘A framework forvulnerability analysis in sustainability science’,Proceedings of the National Academy of Science100(14): 8074–8079

UCS (Union of Concerned Scientists) (2006) ClimateChange in the US Northeast, UCS Publications,Cambridge, MA

UCS (2008) Climate Change in Pennsylvania: Impactsand Solutions for the Keystone State, UCSPublications, Cambridge, MA

UN (United Nations) (1988) Protection of Global Climatefor Present and Future Generations of Mankind, UNGeneral Assembly Resolution, A/RES/43/53, 70thplenary meeting, 6 December 1988, www.un.org/documents/ga/res/43/a43r053.htm, last accessed 6 October 2010

UN (1992) United Nations Framework Convention onClimate Change, www.unfccc.int/resource/docs/convkp/conveng.pdf, last accessed 6 October 2010

UN (1998) Kyoto Protocol to the United NationsFramework Convention on Climate Change,

http://unfccc.int/resource/docs/convkp/kpeng.pdf,last accessed 6 October 2010

UN (2007) Impacts of Climate Change on Peace, SecurityHearing over 50 Speakers, United Nations SecurityCouncil, SC-9000, 17 April, News and MediaDivision, New York, NY

UN (2008) Acting on Climate Change: The UN SystemDelivering as One,www.un.org/climatechange/pdfs/Acting%20on%20Climate%20Change.pdf, last accessed 6 October2010

UN (2009) Global Assessment Report on Disaster RiskReduction: Risk and Poverty in a Changing Climate,ISDR, United Nations, Geneva, Switzerland

UN (2010) World Urbanization Prospects: The 2009Revision, CD-ROM edition, data in digital form(POP/DB/WUP/Rev.2009), United Nations,Department of Economic and Social Affairs,Population Division, New York, NY

UN (undated) Environmental Indicators, United NationsStatistics Division, http://unstats.un.org/unsd/environment/air_greenhouse_emissions.htm, lastaccessed 13 October 2010

UN Millennium Project (2005) Investing inDevelopment: A Practical Plan to Achieve theMillennium Development Goals, New York,www.unmillenniumproject.org/reports/index.htm,last accessed 14 October 2010

UNCTAD (United Nations Conference on Trade andDevelopment) (2009) Financing the ClimateMitigation and Adaptation Measures in DevelopingCountries, Discussion Paper No 57,Intergovernmental Group of Twenty-Four onInternational Monetary Affairs and Development,New York, www.unctad.org/en/docs/gdsmdpg2420094_en.pdf, last accessed 6 October 2010

UNDP (United Nations Development Programme)(2007) Human Development Report 2007/2008,Palgrave Macmillan, New York, NY

UNDP (2009) Human Development Report 2009,Palgrave Macmillan, New York, NY

UNEP (United Nations Environment Programme) (2007)Assessment of Policy Instruments for ReducingGreenhouse Gas Emissions from Buildings, Report forthe UNEP-Sustainable Buildings and ConstructionInitiative, www.unep.org/themes/consumption/pdf/SBCI_CEU_Policy_Tool_Report.pdf, last accessed15 October 2010

UNEP (undated a) UNEP Climate Change Strategy for theProgramme of Work 2010–2011, www.unep.org/pdf/UNEP_CC_STRATEGY_web.pdf, last accessed 6 October 2010

UNEP (undated b) Cities and Climate Change,www.unep.org/urban_environment/issues/climate_change.asp, last accessed 6 October 2010

UNEP, UN-Habitat and World Bank (2010) DraftInternational Standard for Determining GreenhouseGas Emissions for Cities, Presented at 5th WorldUrban Forum, Rio de Janeiro, Brazil, March 2010,www.unep.org/urban_environment/PDFs/InternationalStd-GHG.pdf, last accessed 6 October2010

UNFCCC (United Nations Framework Convention onClimate Change) (1992) United Nations FrameworkConvention on Climate Change, United Nations, NewYork, NY

UNFCCC (1995) Report of the Ad Hoc Group on theBerlin Mandate on the Work of Its First Session Heldat Geneva from 21 to 25 August 1995, http://unfccc.int/cop5/resource/docs/1995/agbm/02.pdf, last accessed28 October 2010

267References

UNFCCC (1996) Report of the Conference of the Partieson Its Second Session, Held at Geneva from 8 to 19July 1996, http://unfccc.int/cop4/resource/docs/cop2/15.pdf, last accessed 6 October 2010

UNFCCC (2004) Guidelines for the Preparation ofNational Communications by Parties Included inAnnex I to the Convention, Part I: UNFCCC ReportingGuidelines on Annual Inventories, Twenty-first sessionon Subsidiary Body for Scientific and TechnologicalAdvice, 6–14 December, Buenos Aires,http://unfccc.int/resource/docs/2004/sbsta/08.pdf,last accessed 13 October 2010

UNFCCC (2007) Investment and Financial Flows toAddress Climate Change, UNFCCC, Bonn, Germany

UNFCCC (2010) ‘UN Climate Change Conference inCancún delivers balanced package of decisions,restores faith in multilateral process’,http://unfccc.int/files/press/news_room/press_releases_and_advisories/application/pdf/pr_20101211_cop16_closing.pdf, last accessed 17 December 2010

UNFCCC (undated a) Status of Ratification of theConvention, http://unfccc.int/essential_background/convention/status_of_ratification/items/2631.php,last accessed 6 October 2010

UNFCCC (undated b) Fact Sheet: An Introduction to theUNFCCC and its Kyoto Protocol, http://unfccc.int/press/fact_sheets/items/4978.php, last accessed 6October 2010

UNFCCC (undated c) Essential Background: Feeling theHeat, http://unfccc.int/essential_background/feeling_the_heat/items/2914.php, last accessed 6 October 2010

UNFCCC (undated d) Fact Sheet: UNFCCC EmissionsReporting, http://unfccc.int/press/fact_sheets/items/4984.php, last accessed 6 October 2010

UNFCCC (undated e) Fact Sheet: What Is the UnitedNations Climate Change Conference (COP/CMP)?,http://unfccc.int/press/fact_sheets/items/4980.php,last accessed 6 October 2010

UNFCCC (undated f) The Special Climate Change Fund,http://unfccc.int/cooperation_and_support/financial_mechanism/special_climate_change_fund/items/3657.php, last accessed 6 October 2010

UNFCCC (undated g) Least Developed Countries Fund,http://unfccc.int/cooperation_support/least_developed_countries_portal/ldc_fund/items/4723.php,last accessed 6 October 2010

UNFCCC (undated h) Chronological Evolution of LDCWork Programme and Concept of NAPAs,http://unfccc.int/cooperation_support/least_developed_countries_portal/ldc_work_programme_and_napa/items/4722.php, last accessed 6 October2010

UNFCCC (undated i) NAPAs Received by the Secretariat,http://unfccc.int/cooperation_support/least_developed_countries_portal/submitted_napas/items/4585.php, last accessed 6 October 2010

UNFCCC (undated j) Adaptation Fund, http://unfccc.int/cooperation_and_support/financial_mechanism/adaptation_fund/items/3659.php, last accessed 6 October 2010

UNFCCC (undated k) Fact Sheet: The Kyoto Protocol,http://unfccc.int/press/fact_sheets/items/4977.php,last accessed 28 October 2010

UNFCCC (undated l) Kyoto Protocol, http://unfccc.int/kyoto_protocol/items/2830.php, last accessed 6 October 2010

UNFCCC (undated m) About CDM,http://cdm.unfccc.int/about/index.html, last accessed6 October 2010

UNFCCC (undated n) Kyoto Protocol JointImplementation, http://unfccc.int/kyoto_protocol/mechanisms/joint_implementation/items/1674.php,last accessed 6 October 2010

UNFCCC (undated o) Constituency Focal Point/ContactDetails, http://unfccc.int/files/parties_and_observers/ngo/application/pdf/const_continfo.pdf, lastaccessed 6 October 2010

UNFCCC (undated p) Non-Governmental OrganizationConstituencies, http://unfccc.int/files/parties_and_observers/ngo/application/pdf/ngo_constituencies_2010_english.pdf, last accessed 6 October 2010

UNFCCC (undated q) Emissions Trading, http://unfccc.int/kyoto_protocol/mechanisms/emissions_trading/items/2731.php, last accessed 28 October 2010

UNFCCC (undated r) Status of Ratification of the KyotoProtocol, http://unfccc.int/essential_background/kyoto_protocol/status_of_ratification/items/5524.php,last accessed 14 December 2010

UNFPA (United Nations Population Fund) (2007) State ofthe World Population 2007: Unleashing the Potentialof Urban Growth, UNFPA, New York, NY

UN-Habitat (United Nations Human SettlementsProgramme) (2003) The Challenge of Slums: GlobalReport on Human Settlements 2003, Earthscan,London

UN-Habitat (2006) The State of the World’s Cities2006/2007: The Millennium Development Goals andUrban Sustainability, Earthscan, London

UN-Habitat (2007) Enhancing Urban Safety and Security:Global Report on Human Settlements 2007, Earthscan,London

UN-Habitat (2008a) Cities in Climate Change Initiative,Nairobi, www.unhabitat.org/pmss/listItemDetails.aspx?publicationID=2565, last accessed 14 October 2010

UN-Habitat (2008b) Gender in Local Government: A Sourcebook for Trainers, UN-Habitat, Nairobi,www.unhabitat.org/pmss/pmss/electronic_books/2495_alt.pdf, last accessed 15 October 2010

UN-Habitat (2008c) Harmonious Cities: State of theWorld’s Cities 2008/2009, Earthscan, London

UN-Habitat (2009a) Planning Sustainable Cities: GlobalReport on Human Settlements 2009, Earthscan,London

UN-Habitat (2009b) ‘Cities and climate change – initiallessons from UN-Habitat’, www.unhabitat.org/pmss/pmss/electronic_promos/2862_alt.pdf, last accessed6 October 2010

UN-Habitat (2010) State of the World’s Cities 2010/2011:Bridging the Urban Divide, Earthscan, London

UN-Habitat (undated) Enhancing the Adaptive Capacityof Arctic Cities Facing the Impacts of Climate Change:Draft Concept Note, UN-Habitat, Nairobi, Kenya

UN-Habitat and OHCHR (2010) Urban IndigenousPeoples and Migration: A Review of Policies,Programmes and Practices, United Nations HousingRights Programme, Report No 8, UN-Habitat, Nairobi,Kenya

UNISDR (International Strategy for Disaster Reduction)(undated a) Secretariat Missions, Functions andResponsibilities, www.unisdr.org/eng/un-isdr/secre-functions-responsibilities-eng.htm, last accessed6 October 2010

UNISDR (undated b) Making Cities Resilient: ‘My City IsGetting Ready’, www.unisdr.org/english/campaigns/campaign2010-2011/

United Cities and Local Governments (undated) ‘United cities and local governments’, www.cities-localgovernments.org/, last accessed 28 October 2010


United Nations Statistics Division (undated) MillenniumDevelopment Goals Indicators, http://mdgs.un.org/unsd/mdg/, last accessed 11 October 2010

United States Conference of Mayors (2008) USConference of Mayors Climate Protection Agreement,www.usmayors.org/climateprotection/agreement.htm,last accessed 6 October 2010

United States Department of Energy (2008) Emissions ofGreenhouse Gases Report, Energy InformationAdministration, www.eia.doe.gov/oiaf/1605/ggrpt/carbon.html, last accessed 13 October 2010

United States Geological Survey (undated) ‘Floods:Recurrence intervals and 100-year floods’,http://ga.water.usgs.gov/edu/100yearflood.html

UN-REDD (United Nations Collaborative Programme onReducing Emissions from Deforestation and ForestDegradation in Developing Countries) (undated)‘About the UN-REDD programme’, www.un-redd.org/AboutUNREDDProgramme/tabid/583/language/en-US/Default.aspx, last accessed 28 October 2010

US Department of Energy (2008) Program Year 2009Weatherization Grant Guidance, WeatherizationProgram Notice 09-1, Department of Energy,Washington, DC, www.waptac.org/si.asp?id=1228,last accessed 17 May 2010

Usavagovitwong, N. and P. Posriprasert (2006) ‘Urbanpoor housing development on Bangkok’s waterfront:Securing tenure, supporting community processes’,Environment and Urbanization 18(2): 523–536

Uyarra, M. C., I. M. Cote, J. A. Gill, R. T. Tinch, D. Vinerand A. R. Watkinson (2005) ‘Island-specificpreferences of tourists for environmental features:Implications of climate change for tourism-dependentstates’, Environmental Conservation 32(1): 11–19

Vaiyda, P. (2010) Climate Impacts in Dhaka, Bangladesh,CIER Document 021710, Division of Research,University of Maryland, College Park, US

Vale, L. and T. Campanella (eds) (2005) The ResilientCity: How Modern Cities Recover from Disaster,Oxford University Press, New York, NY

Valor, E., V. Meneu and V. Caselles (2001) ‘Daily airtemperature and electricity load in Spain’, Journal ofApplied Meteorology 40(8): 1413–1421

van Horen, B. (2001) ‘Developing community-basedwatershed management in Greater São Paulo: Thecase of Santo André’, Environment and Urbanization13(1): 209–222

Van Noorden, R. (2008) Dutch Power Ahead with CarbonCapture, Royal Society of Chemistry, London

VandeWeghe, J. R. and C. Kennedy (2007) ‘A spatialanalysis of residential greenhouse gas emissions inthe Toronto Census Metropolitan Area’, Journal ofIndustrial Ecology 11(2): 133–144

VanKoningsveld, M., J. P. M. Mulder, M. J. F. Stive, L.VanDerValk and A. W. VanDerWeck (2008) ‘Livingwith sea-level rise and climate change: A case study ofthe Netherlands’, Journal of Coastal Research 24(2):367–379

Vecchi, G. A. and B. J. Soden (2007) ‘Effect of remotesea surface temperature change on tropical cyclonepotential intensity’, Nature 450(7172): 1066–1070

Velasquez, L. S. (1998) ‘Agenda 21: A form of jointenvironmental management in Manizales, Colombia’,Environment and Urbanization 10(2): 9–36

Vergara, W. (2005) Adapting to Climate Change: LessonsLearnt, Work in Progress and Proposed Next Steps forthe World Bank in Latin America, World Bank LatinAmerica Region, Sustainable Development Series No25, World Bank, Washington, DC

Wackernagel, M., J. Kitzes, D. Moran, S. Goldfinger andM. Thomas (2006) ‘The ecological footprint of cities

and regions: Comparing resource availability withresource demand’, Environment and Urbanization18(1): 103–112

Wagner, A. (2009) Urban Transport and Climate ChangeAction Plans: An Overview on Climate Change ActionPlans and Strategies from all Continents, SustainableUrban Transport Project (SUTP), GTZ, Germany

Walker, B. and D. Salt (2006) Resilience Thinking:Sustaining Ecosystems and People in a ChangingWorld, Island Press, Washington, DC

Walker, G. and D. King (2008) The Hot Topic: How toTackle Global Warming and Still Keep the Lights On,Bloomsbury Publishers, London

Walraven, A. (2009) The Impact of Cities in Terms ofClimate Change, Report for United NationsEnvironment Programme, Department of Technology,Industry and Economics, Paris, France

Wamsler, C. (2007) ‘Bridging the gaps: Stakeholder-based strategies for risk reduction and financing forthe urban poor’, Environment and Urbanization19(1): 115–142

Wang, M. and H.-S. Huang (1999) A Full Fuel-CycleAnalysis of Energy and Emissions Impacts ofTransportation Fuels Produced from Natural Gas,United States Department of Energy and ArgonneNational Laboratory Center for TransportationResearch, Illinois

Warden, T. (2009) ‘Viral governance and mixed motiva-tions: How and why US cities engaged on the climatechange issue, 2005–2007’, Paper prepared for theFifth Urban Research Symposium, Cities and ClimateChange: Responding to an Urgent Agenda, 28–30June, Marseille, France

Weber, C., G. Peters, D. Guan and K. Hubacek (2008)‘The contribution of Chinese exports to climatechange’, Energy Policy 36(9): 3572–3577

Webster, P., G. Holland, J. Curry and H. Chang (2005)‘Changes in tropical cyclone number, duration, andintensity in a warming environment’, Science309(5742): 1844–1846

WEDO (Women’s Environment and Development Organiz-ation) (2008) ‘Gender, climate change and humansecurity, lessons from Bangladesh, Ghana and Senegal’,Paper prepared for Hellenic Foundation for Europeanand Foreign Policy (ELIAMEP), WEDO, New York, NY

Wheaton, E., V. Wittrock, S. Kulshreshtha, G. Koshida, C.Grant, A. Chapanshi, B. Bonsal, P. Adkins, G. Bell, G.Brown, A. Howard and R. MacGregor (2005) LessonsLearned from the Canadian Drought Years 2001 and2002, Synthesis report prepared for Agriculture andAgri-Food Canada, Saskatchewan Research Council(SRC), Canada

WHEDco (1997) History, Women’s Housing Developmentand Economic Corporation, New York, NY

Wheeler, S. M. (2008) ‘State and municipal climatechange plans: The first generation’, Journal of theAmerican Planning Association 74(4): 481–496

WHO (World Health Organization) (2004) World Reporton Road Traffic Injury Prevention, WHO, Geneva,Switzerland

WHO (2010) Overview of Health Considerations withinNational Adaptation Programmes of Action for ClimateChange in Least Developed Countries and Small IslandStates, www.who.int/phe/Health_in_NAPAs_final.pdf

WIEGO and Realizing Rights: The Ethical GlobalizationInitiative (2009) Women and Men in InformalEmployment: Key Facts and new MDG3 Indicator,WIEGO, Cambridge, MA

Wilbanks, T. (2003) ‘Integrating climate change andsustainable development in a place-based context’,Climate Policy 3(S1): S147–S154

269References

Wilbanks, T. (2007) ‘Scale and sustainability’, ClimatePolicy 7(4): 278–287

Wilbanks, T. and J. Sathaye (2007) ‘Toward an integratedanalysis of mitigation and adaptation: Some prelimi-nary findings’, in T. Wilbanks, R. Klein and J. Sathaye(eds) Mitigation and Adaptation Strategies for GlobalChange 12(5): 713–725

Wilbanks, T. J., P. Romero Lankao, M. Bao, F. Berkhout, S.Cairncross, J. P. Ceron, M. Kapshe, R. Muir-Wood andR. Zapata-Marti (2007) ‘Industry, settlement andsociety’, in M. L. Parry, O. F. Canziani, J. P. Palutikof,P. J. van der Linden and C. E. Hanson (eds) ClimateChange 2007: Impacts, Adaptation and Vulnerability.Contribution of Working Group II to the FourthAssessment Report of the Intergovernmental Panel onClimate Change, Cambridge University Press,Cambridge, UK, pp357–390

Wisner, B., P. Blaikie, T. Cannon and I. Davis (2004) AtRisk: Natural Hazards, People’s Vulnerability andDisasters, second edition, Routledge, London

WMO (World Meteorological Organization) (2007)‘WMO’s role in global climate change issues with afocus on development and science based decisionmaking’, Position Paper CC2, WMO, Geneva,Switzerland, www.wmo.int/pages/themes/documents/FINALPositionpaperrevised19-09-07.pdf, lastaccessed 28 October 2010

Wolf, J., N. Adger, I. Lorenzoni, V. Abrahamson and R.Raine (2010) ‘Social capital, individual responses toheat waves and climate change adaptation: An empiri-cal study of two UK cities’, Global EnvironmentalChange 20(1): 44–52

Wolfe, M. I., R. Kaiser and M. P. Naughton (2001) ‘Heat-related mortality in selected United States cities,summer 1999’, American Journal of ForensicMedicine and Pathology 22(4): 352–357

Women’s Environment Network (2010) Gender and theClimate Change Agenda: The Impacts of ClimateChange on Women and Public Policy,Progressio/Actionaid/World Development Movement,Women’s Environment Network, London

Woodcock, J., D. Banister, P. Edwards, A. Prentice and I.Roberts (2007) ‘Energy and transport’, Lancet370(9592): 1078–1088

World Bank (2000) Republic of Mozambique: APreliminary Assessment of Damage from the Floodand Cyclone Emergency of February–March 2000,World Bank, http://siteresources.worldbank.org/INTDISMGMT/Resources/WB_flood_damages_Moz.pdf, last accessed 13 October 2010

World Bank (2006) World Development Report 2006:Equity and Development, World Bank and OxfordUniversity Press, New York, NY

World Bank (2008) Climate Resilient Cities: 2008 Primer,World Bank, Global Facility for Disaster Reduction andRecovery, and International Strategy for DisasterReduction, www.worldbank.org/eap/climatecities, lastaccessed 14 October 2010

World Bank (2009a) Carbon Finance for SustainableDevelopment: Annual Report 2009, World Bank,Washington, DC, http://siteresources.worldbank.org/INTCARBONFINANCE/Resources/11804Final_LR.pdf,last accessed 28 October 2010

World Bank (2009b) Status on the Special ClimateChange Fund and the Least Developed CountriesFund, World Bank, Washington, DC

World Bank (2009c) World Development Report 2010:Development and Climate Change, World Bank,Washington, DC

World Bank (2010a) A City-Wide Approach to CarbonFinance, World Bank, Washington, DC

World Bank (2010b) State and Trends of the Carbon

Market: 2010, http://siteresources.worldbank.org/INTCARBONFINANCE/Resources/State_and_Trends_of_the_Carbon_Market_2010_low_res.pdf

World Bank (2010c) ‘Global carbon market grows, boost-ing climate action’, http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTSDNET/0,,contentMDK:22591167~menuPK:64885113~pagePK:64885161~piPK:64884432~theSitePK:5929282,00.html, last accessed 15 October 2010

World Bank (2010d) Cities and Climate Change: AnUrgent Agenda, World Bank, Washington, DC

World Bank (undated a) ‘Cities and climate change’,http://siteresources.worldbank.org/WBI/Resources/213798-1259011531325/6598384-1268250262287/WBI_Cities_and_Climate_Change_Brochure.pdf, lastaccessed 28 October 2010

World Bank (undated b) ‘Climate change and the WorldBank’, http://beta.worldbank.org/climatechange/overview, last accessed 28 October 2010

World Bank (undated c) ‘Representative GHG baselinesfor cities and their respective countries’,www.unep.org/urban_environment/PDFs/Representative-GHGBaselines.pdf, last accessed 13 October 2010

World Mayors Council on Climate Change (undated)‘About us’, http://www.iclei.org/index.php?id=10384, last accessed 28 October 2010

World Nuclear Association (2010) World Nuclear PowerReactors and Uranium Requirements – 1 October2010, www.world-nuclear.org/info/reactors.html, lastaccessed 25 October 2010

WRI/WBCSD (World Resources Institute/World BusinessCouncil for Sustainable Development) (undated) TheGreenhouse Gas Protocol: A Corporate Accountingand Reporting Standard, revised edition, WorldResources Institute, Washington, DC, www.ghgprotocol.org/files/ghg-protocol-revised.pdf,last accessed 13 October 2010

Wright, L. and L. Fulton (2005) ‘Climate change mitiga-tion and transport in developing nations’, TransportReviews 25(6): 691–717

Wu, J. and Y. Zhang (2008) ‘Olympic Games promote thereduction in emissions of greenhouse gases inBeijing’, Energy Policy 36(9): 3422–3426

Yarnal, B., R. E. O’Connor and R. Shudak (2003) ‘Theimpact of local versus national framing on willingnessto reduce greenhouse gas emissions: A case studyfrom central Pennsylvania’, Local Environment 8(4):457–469

Ying, S. (2009) ‘A tale of two low carbon cities’, Paperprepared for the 45th ISOCARP InternationalCongress, Low Carbon Cities, 18–22 October, Porto,Portugal

Yuping, W. (2009) ‘Challenge and opportunity on energy-efficiency in building and construction in China’,Paper presented at the Fourth World Urban Forum,Nanjing, November 2008

Zahran S., S. D. Brody, A. Vedlitz, H. Grover and C.Miller (2008) ‘Vulnerability and capacity: Explaininglocal commitment to climate change policy’,Environment and Planning C: Government and Policy26(3): 544–562

Zhang, Z. (2010) ‘Better cities: Better economies’, UrbanWorld 2(4): 56–58

Zhao, J. (2010) ‘Climate change mitigation in Beijing,China’, Unpublished case study prepared for theGlobal Report on Human Settlements 2011,www.unhabitat.org/grhs/2011

Zhao, X. and A. Michaelowa (2006) ‘CDM potential forrural transition in China case study: Options inYinzhou district, Zhejiang province’, Energy Policy34(14): 1867–1882


accountability 28, 117, 133, 136, 151adaptation 1, 2, 5, 9, 10, 14, 15, 122, 124, 129–160,

163, 169, 172–173autonomous 130challenges to 157–159Cities and Climate Change Initiative 22, 146,

152–153and co-benefits 130, 137, 178community-based see community-based adaptationcosts of 154–155, 156, 157, 172, 173defined 129–131and disaster preparedness 137, 144–145effectiveness of 145–153funding for 5, 129, 137, 139, 141, 153–157, 158,

173household 129, 131–133, 152and international climate change framework 21, 22,

24, 26, 28–29and knowledge 130, 131, 133, 134, 144leaders in 167limits of 130and local actors 29, 30and local governance 150–152low priority for 175mal- 131, 170and mitigation 130, 154, 158, 178–179and municipal authorities 129, 130, 131, 137–153national frameworks for 137–138and negative feedback 165–166and partnerships 137, 151planned 130–131policy lessons for 159–160, 179and private sector 28, 130, 151progress towards, markers indicating 141and risk assessment 138–140risks reduced by 130and sea-level rise 142–144sector-specific 147, 148–149, 151and size of cities 86stages of 138, 142triggering events for 145and urban development 177–179and vulnerability 129–130

adaptation deficit 5, 130, 138–140, 150, 154, 156,163, 175

Adaptation Fund 19, 20, 153, 154, 167, 173, 180adaptive capacity 5, 12, 13–14, 15, 27, 70, 80, 138,

165–166factors in 165

aerosols 5, 9, 10affluence 11–12, 92, 125, 165, 172

and adaptive capacity 13–14and consumption 41, 43, 46, 51, 57, 60and waste 44

Africa 6, 45, 68, 73, 78, 98, 125, 156, 157urban population of 3

age see demographic factor

agriculture 8, 10, 34, 35, 38, 44, 48, 51, 60, 75, 105,155, 159

climate change vulnerability of 78, 177air conditioning 3, 10, 11, 39, 43, 52, 66, 72, 76,

113–114air pollution 13, 24, 55, 79, 169

policies to reduce 35, 40, 42, 50, 51, 101, 111, 122air transport 42, 72, 168Akinbami, J. F. 118Antarctica 1, 6, 66Argentina 37, 45

see also Buenos Airesarid regions 6Asia 3, 6, 55, 67–68, 70, 73, 123, 156, 157

megacities in 71, 92Asian Cities Climate Change Resilience Network 26Asian Development Bank 23, 74, 149Asia-Pacific Partnership on Clean Development and

Climate 24Australia 24, 27, 70, 75, 83, 115, 123–124

GHG emissions of 8, 9, 37, 45water demand in 73see also Melbourne; Sydney

aviation 42, 72, 168Aylett, A. 123

Bali Road Map 21Bangkok (Thailand) 37, 39, 41, 44, 46, 71, 138

adaptation measures in 140, 151, 178Bangladesh 13, 14, 37, 45, 68, 81

see also DhakaBarcelona (Spain) 11, 39, 40, 41, 44, 46, 48, 97, 103,

110, 168BASIC countries 49behavioural change 15, 91, 111Beijing (China) 11, 37, 40, 44, 46, 58–59, 99, 102, 123

Olympics (2008) 121Bihar (India) 82, 84biodiversity 3, 26, 77biofuels 38, 39, 43, 97, 99, 103, 110, 118, 124, 174,

177Bogotá (Colombia) 13, 42, 69, 99, 102, 103, 104, 111,

174Boston (US) 69, 70, 72, 95, 99Brazil 3, 29, 43, 70, 78, 84, 103, 123, 124, 180

GHG emissions of 8, 9, 37, 45, 48, 49see also Curitiba; Porto Alegre; Rio De Janeiro; Sao

PauloBritain (UK) 24, 46, 48, 52, 71, 78, 94, 118, 123, 167

GHG emissions of 8, 37, 43, 45mitigation in 96, 174, 180see also London; Manchester

Brookings Institution 47–48brownfield development 41, 94, 95, 124BRT systems see bus rapid transit systemsBuenos Aires (Argentina) 13, 37, 73, 97, 109, 125building codes/standards 87, 97, 108, 145, 152, 169

INDEX

built environment 94–98, 111, 116, 124, 129, 152,171, 176

slow rate of change of 167Bulkeley, H. 26business as usual 120, 126, 141, 164bus rapid transit (BRT) systems 40, 42, 102, 114, 121

C40 (Cities Climate Leadership Group) 26, 92, 96, 105,114, 119, 120

California (US) 13, 25, 40, 71, 167see also Los Angeles; San Francisco

Canada 24, 27, 29, 70, 71, 74, 75, 103GHG emissions of 8, 9, 37, 45, 46land-use planning in 94see also Toronto; Vancouver

Cancún Agreement (2010) 18, 20, 21, 154capacity-building 22, 27, 113–114, 135, 145, 172Cape Town (South Africa) 13, 37, 39, 41, 42, 44, 46, 73

adaptation in 142, 147, 151, 178GHG emissions of 50mitigation strategies in 94, 97, 99, 103, 120, 125

Caracas (Venezuela) 87, 104carbon capture/storage technology 104carbon cycle 4, 5, 11carbon footprint 5, 11, 14–15, 47–48, 58, 110carbon intensity 5, 9, 11, 49, 110, 164, 173carbon leakage 58carbon markets 104, 105, 119–120, 166, 177carbon sequestration 5, 15, 55, 103–105, 124, 171

and co-benefits 122partnerships in 104

Caribbean 23, 76, 77, 78, 85, 125, 156GHG emissions of 8, 45urban population of 3

car-sharing schemes 102, 103CCCI (Cities and Climate Change Initiative, UN-Habitat)

22, 146, 152–153CCP (Cities for Climate Protection) campaign 26, 27,

29, 35, 92, 105, 119, 124Milestone Methodology 93

CDM (Clean Development Mechanism) 20, 24, 29, 44,57, 98, 99, 102, 104, 107, 125, 154, 167

future direction for 180Gold Standard for 117lack of urban projects in 120, 175

CFCs (chlorofluorocarbons) 7, 9Chad 45, 46Chicago (US) 14, 69, 114, 174children 14, 78, 82–83, 170

and poverty 82, 83Chile 13, 45, 70, 120China 24, 29, 39, 58–59, 68, 70, 71, 84, 115, 123, 124

fossil fuels in 52, 176GHG emissions of 8, 9, 11, 37, 43, 44, 45, 46, 48–49Green Lighting Programme 109manufacturing industry in 11, 43, 44, 48, 57National Climate Change Programme 25renewable energy in 97, 99transport emissions in 100urban population of 3water resources of 69, 73see also Beijing; Hong Kong; Shanghai

CHP (combined heat and power) systems 99cities

climate change a low priority in 100, 108, 118, 123,125, 142

compact 48, 54, 55, 70, 94energy demands of 91and hazards 4, 13implications of climate change for 4–10networks of see international city networks

number/size of 2, 86, 165two challenges for 9–10and urban areas, use of terms 36

Cities and Climate Change Initiative see CCCICities for Climate Protection campaign see CCPcities and GHG emissions 2–3, 9–14

and affluence see affluenceas contribution to climate change 33drivers of 10–12, 59–61and economic base 11, 56–57future policy directions for 15, 181–182impacts of see climate change impactsmeasuring see measurement of GHG emissionsopportunities for climate change action 1, 2, 14,

91–92, 170per capita 11, 12, 45, 57scale of 45–52sources of see sources of GHG emissionsvariations in 9, 10, 11, 45–46, 51, 57, 61, 169

city boundaries 36civil society actors 19, 26, 28, 62, 87, 91, 94, 95, 117,

124, 167and adaptation 130–131, 151, 154

Clean Development Mechanism see CDMClimate Alliance 26, 29, 92, 105, 121

Climate Compass 93climate change impacts 65–89, 169–170

definition of terms 65on disaster preparedness 87–88displacement see displacement of peopledrought see droughteconomic 74–78, 86, 169on ecosystem services see ecosystem serviceson energy systems 65, 72–73and exposure levels 86–87, 170extreme heat events see heat wavesfive common themes of 88–89on gender 81–82heavy precipitation events 6, 14, 65, 66, 67–68, 72on industry/commerce 65, 74–75on infrastructure 70–73on insurance 70, 76–77, 80, 131, 150, 170on livelihoods 78long-term 66–67, 88policy lessons from 88–89on poverty see under povertypublic health 78–79on residential/commercial buildings 70–71sea-level rise 1, 3, 6, 65–67social see social impacts of climate changeon tourism/recreation 71, 74, 75–76on transportation systems 71–72, 74tropical cyclones see cyclonestwo categories of 10–11on urban governance/planning see governanceand urbanization see urbanization and climate changeon water/sanitation systems 65, 73

climate change science 18, 21, 30, 117, 180climate change terminology 5climate system 4–6climatic factor in energy use 5, 52, 72, 169Clinton Climate Initiative 26, 95, 96, 113, 114CO2 (carbon dioxide) 5

emission reduction targets 24–25emissions per capita 45global concentration/lifetime in atmosphere 7, 67global warming potential of 6, 7sources of 7, 8urban contributions to 9, 10, 52

coal 8, 11, 38, 39, 42, 43, 52coastal areas 1, 3, 4, 66, 68, 71, 74, 76, 78, 87, 139, 155


insurance cover in 77and poverty 80vulnerability of see sea-level rise

coastal erosion 71, 76, 78co-benefits 122, 125, 130, 178, 179Colombia 145, 151

see also Bogotá; Manizalescombined heat and power (CHP) systems 99commercial buildings see residential/commercial build-

ingscommunications 3, 74community-based adaptation 130–131, 134–137,

147–148, 151, 152, 160, 172, 178challenges of 136–137

community-based organizations 27, 94, 113, 134–135,150

community-based risk assessment 134, 147community engagement/capacity 134compact cities 48, 54, 55, 70, 94composite urban form 56concatenated hazards 13, 165congestion charges 101, 102, 108, 110construction industry 10, 77, 96–97consumption-based approach 10, 11, 33, 36, 57,

58–59, 106, 169consumption patterns 15, 33, 34, 55, 59–60, 169Cool Earth Partnership 24Copenhagen Accord (2009) 18, 21, 23, 91, 173, 176coral reefs 1, 66, 75, 76, 78, 164corporations 34–35, 43, 119corruption 86, 89, 111, 117Cuba 3, 88Curitiba (Brazil) 54, 102cycling/walking 42, 55, 56, 60, 61cyclones 1, 3, 4, 6, 65, 66, 67

early warning system for 13Czech Republic 37, 45

see also Prague

Dalal-Clayton, B. 138Dar es Salaam (Tanzania) 42, 44, 133, 136, 139, 178deforestation 4, 7, 10, 55, 176Delhi (India) 11, 37, 110, 111democracy 141, 145demographic factor 14, 53–54, 61, 165, 169

climate change impacts on 82–84, 170Denver (US) 37, 39, 41, 46DesInventar methodology 147developed countries 14–15, 25, 29, 170

access to electricity in 39–40adaptation in 142–145, 150GHG emissions of 8, 9, 11, 44, 46–48, 60, 159, 163industry in 43mitigation in 94, 96–97, 123–124urbanization in 2, 3

developing countries 9, 25, 29, 163, 170adaptation in 129, 130, 131, 138–142, 150,

153–154, 156–157, 175bus rapid transit systems in 40carbon sequestration in 104car use in 41–42emissions targets for 57GHG emissions of 48–51, 159industry in 43lack of resources in 86, 94mitigation in 92, 97, 123, 124, 175private transport in 100–101, 171slums in see slumsurbanization in 1, 2, 3, 86women in 82

development banks 23, 74, 107, 110

development deficit 154, 156, 175development paths 9, 142, 164, 165, 173, 174,

176–177, 180, 181Dhaka (Bangladesh) 12, 14, 27, 37, 51, 71, 103

adaptation in 139, 140, 172, 178impacts of cyclones in 74Korail informal settlement 132, 133, 134

disaster preparedness 13, 27, 29, 69, 87–88, 89, 134,146, 147

infrastructure maintenance 87disaster relief programmes 84, 136, 152

women and 82disaster risk reduction 22, 24, 26, 28, 29

and adaptation 135, 136, 141, 144–145disasters, increasing frequency of 1–2, 3, 6, 13, 87–88,

164disease 3, 78, 79, 82, 83, 86displacement of people 65, 74, 78, 82, 84–85, 146,

149, 159, 169, 173see also migration

drainage systems 3, 5, 66, 68, 74, 139, 141, 144, 146,150, 151

and poverty 14, 68, 80, 132, 133–134drought 1–2, 3, 6, 66, 70, 74

and adaptation 144, 146and migration 84

drylands 3, 4Durban (South Africa) 77, 111, 117, 124, 125, 167,

169adaptation in 141–142, 147, 151, 175, 178, 179

early warning systems 1, 3, 13, 14, 80, 136eco-cities 55, 94–95ecological footprint 5, 58ecological modernization theory 11–12economic development 9, 10, 11–12, 46, 86, 122, 165,

166and adaptation 129, 137, 144, 156–157, 158

economies of scale 3, 13, 53, 55, 60, 104, 165ecosystem loss see environmental degradationecosystem services 3, 65, 77, 92, 143ecozones 3, 4Ecuador 69, 99, 120, 153education 13, 14, 22, 51, 58, 107, 115

and adaptation 151of children 78, 81, 82

Egypt 66, 102, 104elderly people 70, 83–84electricity generation/consumption 38–40, 44, 46, 50

access issue 40inter-city variations in 39

El Salvador 134emissions certificates 24emissions inventories 10, 34, 36, 42, 58

for cities 42, 46, 47, 49, 117omissions from 42, 47, 49, 57

emissions targets 24–25, 46, 47, 57, 91, 93, 117, 176emissions trading 20–21, 24, 29, 119–120, 167employment 14energy costs/prices 176–177energy demand/use 11, 72, 88, 91, 164, 168

measures to reduce 97women and 97

energy efficiency 15, 24, 43, 86, 91, 93–94, 95, 96–98,108, 110, 119, 171, 173

clubs 111and co-benefits 122limitations of 98, 100and rebound effect 98, 100, 105, 174standards 115, 116–117, 174three policy approaches of 96

273Index

energy generation 8, 10, 33, 34, 35, 38–40, 51, 148climate change impacts on 65, 72–73decentralized 97, 110, 113and mitigation 98–100, 106, 176production/consumption perspectives on 60and water resources 72see also electricity generation/consumption;

renewable energyenergy intensity 5, 43energy security 23, 24, 29, 99, 100, 110, 171environmental degradation 11, 12, 48, 66, 77, 88

and migration 84, 159environmental justice 9, 96, 159Environmental Kuznets Curve 11–12equity 1, 12, 163, 166Estonia 45, 76Ethiopia 45, 68, 70ethnic minorities 2, 84, 87, 88, 170Europe 3, 6, 67–68, 78, 124–125

heat wave in 69, 70, 145scale of urban emissions in 45, 48

European Emissions Trading Scheme 24, 29, 167, 174European Union (EU) 23, 24, 26, 116, 167

financial capital 13, 78, 86, 165Finland 37, 45, 116flash floods 68, 87, 144floods/flood risk 1, 3, 12, 13, 68

100-/500-year 70–71adaptation to 15, 87, 130, 132–134, 139–140, 146,

149, 150costs of 70, 71, 72, 78developing countries’ vulnerability to 68and ethnic minorities 84and exposure 87and insurance 76, 77and migration 84most exposed cities 4, 71and poverty 14, 80, 87, 132–133and resilience 149

fluorinated gases 6, 8food production/distribution 22, 33, 44, 51, 59, 177forests/forestry 4, 8, 34, 35, 44, 51, 60

and mitigation 103, 105, 106, 177fossil fuels 7, 38–39, 176

see also coalFrance 8, 37, 45, 69, 70, 81

see also Parisfuel poverty 94, 98

garden cities 104gender inequities 2, 11, 12, 60, 104

aspects of 81climate change impacts on 81–82, 170in disasters 14and mitigation 92, 96and transport 101

Geneva (Switzerland) 37, 39, 41, 42, 44, 46, 48geographical factors 3, 11, 52–53, 61, 164, 169Georgetown (Guyana) 138–140, 149Germany 24, 46, 68, 96, 99

GHG emissions of 8, 12, 37, 45mitigation strategies in 96, 99, 102, 167, 174, 180

Ghana 84, 132GHGs (greenhouse gases) 2–3, 4–10, 164–165

allocation of responsibility for 33, 51, 57, 61, 92,160, 166

characteristics of 7contribution to climate change of 9–10demographic factor in 14, 53–54, 61and gender inequities 11

geographical factors in 3, 11, 52–53, 61global/national emissions of 8, 9, 38, 45–52global warming potential of 6–7, 9growth in emissions of 45–46, 164lifetime in atmosphere/time-lag in reducing 7, 67,

130measuring see measurement of GHG emissionsmitigation see mitigationnational/regional variation in emissions of 45–46, 61,

169sources/levels of see sources of GHG emissionsand urban economy 56–57, 61and urban form/density 54–56see also CO2; methane; nitrous oxide

glacial melt 6, 65, 69, 73Glasgow (UK) 37, 46, 48global warming 4–5, 6–7, 65

see also greenhouse effectgovernance 2, 28, 87, 89, 106, 115–123, 164,

171–172and adaptation/resilience 150–152autonomous 115, 116, 126, 151financial resources for 118–120four modes of 107–114, 171and infrastructures/cultural practices 118institutional factors in 115–117and issue-framing/co-benefits 122leadership and 120–121multilevel 25–26, 115–116, 174and policy implementation/enforcement 116–117political factors in 120–123scientific knowledge and 117technical/material/financial factors in 117–120and urban political economies 122–123

Greece 12, 37, 110greenhouse effect 4–10

gases involved in 6–10greenhouse gases see GHGsgreen urban spaces 70, 94, 104, 146Guangzhou (China) 68, 71Guyana 138–140, 149

halocarbons 6, 7, 9hazard maps 134, 136, 138, 140, 142, 147health 3, 13, 42, 139, 145, 146, 148, 152, 155

climate change impacts on 78–79, 86, 88and poverty 79see also disease

heating/cooling systems 7, 10, 11, 37, 42, 72, 91, 164combined heat and power (CHP) systems 99district 110, 118and urban density 55

heat waves 6, 12, 14, 69–70, 78, 83adaptation to 15, 144, 145and poverty 80

heavy precipitation events 6, 14, 65, 66, 67–68, 72,169

HFCs (hydrofluorocarbons) 6, 7Ho Chi Minh City (Viet Nam) 68, 71Hodgkinson, D. 159Hong Kong (China) 45, 58, 71, 111households 39–40, 43, 55, 60

and adaptation 129, 131–133, 152GHG emissions of 10, 11, 12, 33size 53, 169women in 81–82, 97

housing see residential/commercial buildingshuman capital 13, 86, 165Hungary 151hydropower 39, 43, 46, 48, 53, 72Hyogo Framework 22, 167


ICLEI (Local Governments for Sustainability) 26, 27, 29,92, 114, 119, 174, 176

Cities for Climate Protection campaign see CCPemission measurement methodology of 35

Ilo (Peru) 27, 178impact assessments 137–138income see livelihoods/incomeIndia 24, 25, 29, 68, 72, 82, 84, 94, 98, 123, 124, 132,

134energy consumption in 43GHG emissions of 8, 33, 37, 38, 48, 49transport emissions in 100urban population of 3, 80see also Delhi; Kolkata; Mumbai

Indian Ocean 66, 67indigenous people 26, 27, 84, 87, 88, 89Indonesia 71, 81, 99, 100–101, 109, 123

GHG emissions of 8, 45industrialization 13, 57, 123, 165industry 8, 9, 10, 60, 106, 168, 176

climate change impacts on 65, 74–75energy intensive 43, 74GHG emissions by 43–44, 51, 57, 164international shifting of 11–12, 34, 43, 48, 53, 57,

92, 169production/consumption perspectives on 60variations in emissions by 43, 169

inequality and climate change 86, 95, 100informal settlements see slumsinformation 130, 131, 133, 134, 144, 147, 167, 172,

180access to 117transfer/sharing 27, 30, 61, 174

infrastructure 2, 15, 29, 60, 98, 164, 171and adaptation 129, 130, 134, 136, 139, 142, 144,

145, 148–149, 154, 155, 158, 178climate change impacts on 70–73, 86, 170and co-benefits 122deficits 156–157, 172investment 149, 150and mitigation 98–100, 109–110, 115, 118, 124and partnerships 112, 113vulnerability of 72, 73, 88

innovation 1, 3, 164input-output analysis 58institutions 129, 130insurance 70, 76–77, 80, 131, 150, 170international agencies 98, 131, 146, 152–153, 156,

158international city networks 25–27, 29, 61, 87, 92, 105,

120–121, 167mitigation initiatives of 114, 115, 124, 125, 174

international climate change framework 17–30, 91,166–167

bilateral initiatives 24challenges/opportunities in 24–25, 28–29, 30future policy directions of 180international-level actors in 21–24Kyoto Protocol see Kyoto Protocollocal-level actors in see local-level actorsmilestones in 18national-level actors in 24–25OECD in 23regional development banks in 23regional/supra-national initiatives 24role of cities in 17, 30structure of 17United Nations Framework Convention on Climate

Change see UNFCCCInternational Standard for Determining Greenhouse Gas

Emissions for Cities 22, 23, 33, 36, 105

investment 28, 33, 122, 155–157, 173IPCC (Intergovernmental Panel on Climate Change) 5,

6, 17, 38–39, 66, 70, 145, 160, 164, 166, 174,180

and adaptation/resilience 129, 131, 149inventories criteria of 34, 36role/activities of 18, 28

iron/steel industry 43, 74, 105island states 24, 66, 76, 85, 154, 176Israel 96Italy 70, 78, 86, 121, 149

GHG emissions of 8, 37, 45see also Milan; Rome

Jakarta (Indonesia) 71, 123Japan 24, 68, 87, 100

GHG emissions of 8, 37, 45Johannesburg (South Africa) 50, 56, 99, 100, 104, 109,

116, 120joint implementation mechanism 20, 29Jordan 37

Kampala (Uganda) 87, 132, 153Katrina, Hurricane (2005) 2, 75, 76, 77, 79, 84, 88Kennedy, C. 57Kenya 22, 45, 87King, D. 57knowledge see informationKolkata (India) 11, 37, 68, 71Kopets, A. 118Korea, Republic of 24, 180

GHG emissions of 8, 37, 45, 46see also Seoul

Kyoto Protocol (1997) 15, 17, 18, 20–21, 24, 30, 34,57, 115, 124, 166, 175, 177

COPs (Conferences of the Parties) 21developed/developing countries roles in 20flexible mechanisms of 20, 23, 29stalemate in negotiations 20targets in 91

Kyrgyzstan 97

Lagos (Nigeria) 27, 100, 104, 122, 125, 132, 133–134,139, 172, 178

landfill 10energy from see methane capture/storage

landslides 3, 13, 68–69, 72land use 3, 4, 7, 10, 11, 12, 34, 35, 86

and exposure 87, 170and GHG emissions 38, 44, 164mixed 40, 54, 55

land-use planning 29, 41, 62, 87, 141, 152and mitigation 91, 94–95, 108, 110, 115

land-use zoning 88, 94, 99, 117, 145, 152, 174Latin America 23, 68, 73, 85, 98, 123, 125, 144, 147,

156GHG emissions of 8, 45urban population of 3

Lawal, A. 118leadership 15, 120–121, 167, 174least developed countries 2, 3, 44, 84Least Developed Countries Fund 19, 29, 154Liberia 45, 46lifestyle 15, 94lighting 43, 52, 60, 61

energy-efficient 109, 119non-electric 39, 40

Lima (Peru) 69, 104, 111, 120Lisbon (Portugal) 48livelihoods/income 9, 41, 43, 53, 55, 60, 61

climate change impacts on 78, 86

275Index

diversity of sources of 86Ljubljiana (Slovenia) 37, 110local government see municipal authoritiesLocal Governments for Sustainability see ICLEIlocal-level actors 17, 25–29, 30, 57

and adaptation see community-based adaptationand city networks 25–27, 29, 61, 87and international framework 28–29, 168NGOs 27–28private sector 28

London (UK) 11, 37, 39, 40, 41, 44, 46, 48, 55, 56, 72,167, 169, 179

adaptation in 142–143, 147, 151, 157, 158GHG inventory of 42mitigation in 96, 101, 110, 116, 117, 118, 120, 168,

174public–private provision in 113

Los Angeles (US) 37, 39, 41, 43, 44, 46, 71, 79, 110political leadership in 121

low-carbon vehicles/fuels 101, 102–103, 109, 118, 173

maladaptation 131, 170malaria 79, 82, 83, 87Malawi 86malnutrition 83Manchester (UK) 94, 96, 99, 114Manila (Philippines) 71, 78Manizales (Colombia) 27, 151, 169, 175, 178Maputo (Mozambique) 78, 132, 153maritime transport 42, 168Marrakesh Accords (2001) 19, 20mayors 27, 120, 147, 167Mayors Climate Protection Agreement (US) 25, 27, 123Mayors, Covenant of (EU) 26MDGs (Millennium Development Goals) 26, 157, 158measurement of GHG emissions 10, 11, 22, 33–36, 61,

105, 168–169boundary issues in 36, 61, 168consumption-/production based 33, 36, 58–59, 169corporate 34–35and developing countries 48international protocols for 34local government 35–36national inventories 10, 34, 36, 42new baseline/standard in 36, 37omissions in 42, 47, 49, 123politics of 57–61scope concept in 35, 36, 57, 58sectors assessed in 34, 51, 61UNFCCC criteria 33–34

Mediterranean 3, 6, 76megacities 71, 92, 119, 125Melbourne (Australia) 13, 73, 99, 109, 110, 117

adaptation strategy in 143–144, 147, 178methane (CH4) 5, 6, 7, 44methane capture/storage 44, 49, 98, 99, 100, 119–120,

168, 174Mexico 25, 29, 70, 123, 124, 151, 152

flash floods in 68GHG emissions of 8, 37, 45, 49, 50

Mexico City (Mexico) 11, 12, 37mitigation strategies in 25, 97, 99, 102, 110, 119, 120

Miami (US) 71, 82migration 65, 74, 78, 82, 84–85, 89

internal 84, 159predicting patterns of 85see also displacement of people

Milan (Italy) 101, 103Millennium Development Goals see MDGsMillennium Ecosystem Assessment 77Mitch, Hurricane 14, 73, 145

mitigation 1, 5, 9, 10, 14, 15, 91–126, 163, 170–172and adaptation 130, 154, 158, 178–179assessing impacts of 105–106comparative analysis of 123–125and consumer choice 33in developed/developing countries 92, 94and four modes of governing 107–114and governance see governanceidentifying/prioritizing actions 106and international climate change framework 21, 22,

24, 26, 28issue-framing/co-benefits of 122, 125leaders in 167and local authorities/actors 29, 30, 61, 91, 92–106‘low hanging fruit’ of 105, 125, 126‘nationally appropriate’ 49opportunities/constraints for 91–92, 100, 110, 111,

115–123, 124, 125, 170–171, 173–176policy lessons for 125–126, 179and poverty 80–81and private sector 28, 91, 94–95, 98, 119production/consumption perspectives on 106regulation and 102, 103, 108, 110trigger events for 121–122and urban density/form 2, 12, 56, 86, 94–95, 124and urban development 176–177, 178–179and urban governance 107–114, 115–117and vulnerable groups 92and women 97

mobilization 112, 113–114, 171monitoring 93, 117, 134, 152monocentric urban form 56Monstadt, J. 92Montreal Protocol (1987) 9Mozambique 45, 73, 78, 87, 132, 153Mumbai (India) 12, 13, 41, 56, 68, 71, 87

mitigation strategies in 103, 113, 114, 122women waste pickers in 99

municipal authorities 25, 26, 28–29, 57–58, 163and adaptation 130, 131, 136, 137–153, 154, 158,

177–179ad hoc/strategic approaches of 93–94, 120, 171and built environment 94–98and carbon sequestration 103–105emissions scopes for 36energy efficiency and 93–94financial resources of 118–120, 174–175and four modes of governing 107–114measuring GHG emissions of 35–36mitigation responses by 91–106, 107, 176–177,

178–179in partnerships see public–private partnershipspolicy approaches of 93–94policy lessons for 61, 62, 181–182and transport 100–103and urban development/design 94–95and urban infrastructure 98–100and waste management 100

municipal buildings/vehicle fleets 35, 47, 57, 62,102–103, 109

NAPAs (National Adaptation Programmes of Action) 19,25, 29, 86, 138, 153, 157

national governments 10, 13, 17, 24–25, 28–29, 34,89, 91

and adaptation 130, 137–138future policy directions for 180–181and municipal authorities 22, 27, 29, 61, 115–116,

119national inventories 10, 34, 36, 42natural capital 13, 78, 165


natural gas 8, 11, 36, 39, 41, 42–43, 46, 52for vehicles 103

Nepal 37, 82, 83Netherlands 37, 45, 68, 96

see also RotterdamNew Orleans (US) 68, 73, 74, 75

see also Katrina, HurricaneNew York City (US) 11, 13, 37, 39, 40, 41, 44, 56, 57,

68, 95, 96, 118, 168, 169, 179emissions in 47GHG inventory of 42, 46, 47vulnerability to floods of 68, 73

New Zealand 71, 83, 124NGOs (non-governmental organizations) 21, 26, 27–28,

29, 30, 87, 95, 107, 133, 151, 153, 167future policy directions for 182–183

Nigeria 116–117, 118, 176see also Lagos

nitrous oxide (N2O) 6, 7, 8–9, 13North Africa 66, 70North America 6, 54, 67–68, 69

scale of urban emissions in 45, 46–48urban population of 3

North Atlantic 66, 67Norway 12, 37, 45, 75, 167nuclear power 39, 46, 48, 72, 99

OECD (Organisation for Economic Co-operation andDevelopment) 19, 23–24, 52, 81, 97, 137

oil industry 75overseas development assistance 154, 173ozone depletion 9

Pacific region 65–66Pakistan 69, 79, 84Paris (France) 37, 69, 103, 110partnerships see public–private collaborationpassive solar design 55pedestrians 103, 122perfluorocarbons 6peri-urbanization 54Peru 27, 69, 104, 111, 120, 178Philadelphia (US) 37, 69, 94, 96, 103Philippines 84, 87, 123, 135, 147, 148, 153

see also Manila; Sorsogon Cityplanned adaptation 130–131planning regulations 94, 107polar ice melt 1policy environment 57–58pollution 1, 4, 13, 24, 42, 50, 73

see also air pollutionpolycentric urban form 56population density see urban densityPorto Alegre (Brazil) 103, 122, 123Portugal 37, 48poverty 2, 12, 13, 14, 50, 61, 122, 166

and adaptation 70, 80, 130, 132–133, 137, 152and age 82, 83–84alleviation 14, 24, 40, 137climate change impacts on 65, 68–69, 77, 78, 79–81,

88and public health 79reasons for vulnerability of 80

Prague (Czech Republic) 37, 39, 41, 42, 43, 44, 46, 48precipitation see heavy precipitation eventsprivate sector 28, 62, 91, 94, 98, 102, 107, 119

and adaptation 28, 130, 151and future policies 182, 183

privatization 28, 98, 113production-based approach 10, 11, 33, 36, 58–59, 106,

169

production-oriented cities 58–59pro-poor policies 27, 137psychological vulnerability 82public awareness 21, 22, 26, 58, 100, 108public health see healthpublic–private partnerships 22, 28, 62, 91, 94, 102,

108, 125, 166, 172, 176three modes of 112–114

public transport 1, 40, 42, 46, 72, 152, 174bus rapid transit (BRT) systems 40, 42, 102, 114and mitigation strategies 101–103, 110, 124–125and urban density 56, 61

Puerto Rico 134, 147pulp/paper industry 43, 51, 74

Qatar 45quality of life 1, 3, 14, 40, 61, 178Quito (Ecuador) 69, 99, 120

railways 34, 72, 110rainfall see heavy precipitation eventsrebound effect 98, 100, 105, 174reforestation 103–104refugees 159regional development banks 23renewable energy 39, 53, 96, 97, 98, 110

for vehicles 101, 102–103, 171see also biofuels

residential/commercial buildings 42–43, 51, 60, 95–97,106, 111, 168, 178

climate change impacts on 70–71and energy efficiency/sustainability 43, 96, 97and income level/house size 43, 46retrofitting 96, 97, 98, 109, 129, 149traditional design/materials 97, 118see also households

residual damage 130, 154, 155, 156, 159, 173, 178resilience 3, 5, 12–14, 27, 86, 169, 170

and adaptive capacity 13–14, 130, 131, 134–135,149–150

asset-based framework for 136, 137defined 130, 149and hazards/disaster recovery 12and urban governance 87

resource scarcity 85, 88, 89, 144retail sector 74, 170Revi, A. 80Rio De Janeiro (Brazil) 13, 37, 44, 46, 53, 56, 76

mitigation strategies in 97, 99, 104, 122, 123, 125risk see vulnerabilityrisk assessment 134, 138–140, 147, 158, 175roads 71–72, 152, 158Rome (Italy) 101, 102, 103Romero Lankau, P. 116Rosenzweig, C. W. 25Rotterdam (Netherlands) 37, 68, 96, 104, 142, 144Russia/Russian Federation 75, 94

GHG emissions of 8, 45Rutland, T. 123

saltwater intrusion 1, 3, 71, 73San Francisco (US) 37, 95, 103, 119sanitation 14, 29, 54, 55, 61, 98, 148, 151, 169

climate change impacts on 68, 73, 79, 170Santiago (Chile) 13, 120São Paulo (Brazil) 9, 11, 26, 37, 44, 46, 83

GHG emissions of 49, 53, 57mitigation strategies in 97, 99, 102, 104, 110,

119–120, 122, 123Saudi Arabia 8, 45savings schemes 132, 133, 134–136, 150

277Index

Schwaiger, B. 118science–policy interface 18, 30sea-level rise 1, 3, 6, 65–67, 87, 169

and adaptation 142–144, 149developing countries’ vulnerability to 68direct/indirect effects of 66, 71, 73, 78long-term event 66–67and migration 84

security issues 85, 89self-governing 107, 108, 109, 171self-sufficiency 60Seoul (Republic of Korea) 37, 40, 46, 110service-based economies 11–12, 58service sector 10, 11, 14, 15, 56Setzer, J. 26Shanghai (China) 11, 13, 37, 40, 44, 46, 58–59, 68, 71,

123, 168eco-city in 94–95

Singapore 37, 45, 56, 58, 104, 118, 149Slovenia 37, 110slums 1, 13, 14, 54, 68–69, 69, 74, 78, 80, 86, 89,

139, 171and adaptation 131, 132–134growth of 91, 94upgrading 134, 148, 152vulnerability of 87, 88, 89, 94

social capital 13, 136, 165social equity 1, 12, 125social housing 110social impacts of climate change 79–84, 89, 110, 169,

176on age 82–84on gender 81–82on minority groups 84on poverty see under poverty

social justice 2, 96social learning 151social relationships 13, 78solar power 97, 110Sorsogon City (Philippines) 22, 153sources of GHG emissions 33, 36–44, 51, 165,

168–169agriculture/land-use change/forestry 44commercial/residential buildings 42–43energy generation 38–40industry 43–44and mitigation potential 38transport 40–42waste 44

South Africa 43, 56, 121, 123, 124, 125, 169adaptation in 140–142emissions from industry in 44, 48, 49GHG emissions of 8, 37, 45, 49–51see also Cape Town; Durban; Johannesburg

South Asia 45, 55, 178Southeast Asia 41, 54, 55, 78Spain 8, 37, 70

see also BarcelonaSpecial Climate Change Fund 19, 154Sri Lanka 37, 45stakeholder participation 25, 30

and adaptation 141, 142, 147and mitigation 91, 95, 100, 104, 111, 114, 126

Stern, N. 150Stockholm (Sweden) 11, 37, 95, 96, 101, 102–103,

174storms 1, 6, 12, 78–79, 87

early warning systems for 3, 13, 14, 80and insurance 76see also cyclones

street lighting 35, 42, 99, 122

sub-Saharan Africa 3, 14, 54, 59, 178subsidence 71suburbanization 44, 54Sugiyama, N. 116sustainable development 2, 15, 95, 97, 117, 122, 163,

166Sweden 12, 37, 59, 101, 115, 174

see also StockholmSwitzerland 37, 69, 116

see also GenevaSydney (Australia) 37, 73, 99, 113

Takeuchi, T. 116Tanzania 42, 44, 133, 136, 139, 178Tatabánya (Hungary) 151taxation mechanisms 24, 57–58, 102, 108, 110technology transfer 22Tel Aviv (Israel) 96temperature rise see global warmingThailand 14, 37, 45, 46, 67, 68, 94, 134tipping point 5Tokyo (Japan) 11, 37, 40, 46, 57, 60–61, 71Toronto (Canada) 37, 39, 40, 41, 43, 44, 55, 94, 114

CO2 emissions target for 46tourism 47, 66, 71, 74, 75–76, 78, 86, 148, 177transition towns 113transit-oriented development 40transparency 28, 34, 151transport 2, 3, 12, 148, 165, 168, 171

climate change impacts on 71–72, 74demand-reduction/-enhancement initiatives 103emissions by 7, 8, 10, 33, 38, 40–42, 46–47, 48, 50,

51five Ds of 40and gender 101infrastructure 102inter-city variations in 40, 41low-carbon vehicles/fuels 101, 102–103, 109, 118,

173and mitigation 94, 100–103, 105, 106, 110, 123,

171, 176modes 42partnerships in 102, 103pedestrians and 103, 122planning 15, 40–41private car ownership/use see vehicle ownershipproduction/consumption perspectives on 60public see public transportregulatory measures in 102, 103, 110–111sustainable 55and urban form/density 55, 56

UCLG (United Cities and Local Governments) 26Uganda 87, 132, 153Ukraine 8, 118UNEP (United Nations Environment Programme) 6, 18,

21–22, 29UNFCCC (United Nations Framework Convention on

Climate Change) 9, 17–20, 25, 29, 30, 163,166–167

allocation of responsibilities in 33, 160, 166Annex I/II countries 19COPs (Conferences of the Parties) 19, 20, 153–154,

166estimates of investment needs 155, 156, 157funding mechanisms of 19, 28, 153–154, 175history/aims of 17, 91key challenge for 19–20and local authorities 29and national inventories 33–34, 58and NGOs 27


norms/principles in 17–19UN-Habitat 22, 146, 150, 152–153, 160

see also CCCIUNISDR (United Nations International Strategy for

Disaster Reduction) 22United Nations (UN) 21–23, 166

coordination activities 21and disaster risk management 22five focus areas for 21, 22partnerships and 22

United States (US) 3, 69, 70, 72, 78, 99, 103civil society in 95climate change legislation in 25climatic factor in 52disaster preparedness of 88emissions from transport in 40, 46–47energy demand in 72Energy Dept. 96, 99flood risk/sea-level rise in 68, 71, 73fossil fuel consumption by 42–43GHG emissions of 8, 9, 11, 37, 45, 46–48, 61, 159GHG inventories in 42, 46insurance industry in 76and international climate change framework 21, 24inter-state initiatives in 25mitigation strategies in 95, 96, 115, 119, 123tourism in 75urban density in 55see also California; Denver; New Orleans; New York

City; Washington DCurban areas see citiesurban density 2, 3, 12, 15, 43, 46, 48, 54–56, 61, 169

by region/national income 54and climate 55and GHG emissions 55–56measurement of 54and mitigation policies 56and transport emissions 40, 55and vulnerability 55, 88and waste 44

urban development/design 3, 15, 94–95, 124, 129urban form 12, 15, 54–56, 61, 169

four types 56and mitigation 94–95, 118slow rate of change of 167spatially compact/mixed-use 54–55sustainable, seven design concepts for 55and transport 40

urban governance see governanceurban heat-island effect 13, 55, 69–70, 73, 78, 86, 88,

142, 169measures to reduce 149

urbanization and climate change 1–3, 10, 36, 65,85–86, 92, 123, 157

co-evolving relationship in 2, 9, 11and ecozones 3, 4hazards of 1–2, 68–69, 164–165and land-use changes 11opportunities for 1, 2, 14, 163, 165six aspects of 2–3

urban planning 3, 15, 88, 89, 175urban population growth 2, 3, 4, 44, 53–54, 88, 91,

173

urban resilience 3, 12–14urban sprawl 12, 44, 48, 54, 94, 118, 170–171urban village model 56

Vancouver (Canada) 37, 94, 149VandeWeghe, J. R. 57vehicle ownership 40, 41–42, 59–60, 94, 100–101

and gender 101Venezuela 87, 104Venice (Italy) 78, 86, 149Viet Nam 68, 71, 73, 149voluntary approaches 112–113, 115, 117, 171–172vulnerability 5, 12–14, 15, 61, 85–88, 170

and adaptation 129–130, 131assessments 80, 134, 138–140, 147, 158, 160and disaster preparedness 87–88and economic development 86and exposure levels 4, 71, 86–87, 170groups at risk 14, 68–69, 77, 88, 147, 170maps 134, 136, 138, 140, 142, 147and mitigation 92sector-specific 147and urban density 55and urban development 13and urban governance/planning 87and urbanization 85–86

Walker, G. 57Warden, T. 27Washington DC (US) 11, 37, 40, 46, 57, 73waste 10, 11, 34, 35, 38, 44, 51, 60, 152, 168

energy from 44, 49, 98, 99–100, 119management/reduction 100and mitigation 91, 98, 99–100, 105, 106, 120, 124,

168wastewater treatment 28, 34, 35, 47, 48, 49, 106, 146,

152water efficiency 86, 96, 98, 106, 108, 112, 119, 144,

145, 148, 149water resources/supplies 6, 12, 53, 65, 69, 73, 85, 86,

124and adaptation 135, 141, 144, 145, 146, 148, 149climate change impacts on 73, 88, 170and energy generation 72sustainable 96–97, 98

water vapour 6weather-related stresses 1, 2, 3, 6, 12, 13, 66

adaptation to 15, 131–132see also drought; heavy precipitation events; storms

wetlands 3, 8, 11, 34, 66, 77, 87, 141, 169wind power 99WMO (World Meteorological Organization) 18, 22women 2, 11, 12, 14, 60, 81–82, 89

organizations for 87, 99, 134and transport 101vulnerability of 81

World Bank 23, 29, 81, 149

Yemen 45, 70Yogyakarta (Indonesia) 100–101, 109

Zambia 45, 46

279Index

Cities and climate chnage alt[1]

Technology

Transcript of Cities and climate chnage alt[1]